{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "MNIST classification (drawn from sklearn example)\n",
    "=====================================================\n",
    "MWEM is not particularly well suited for image data (where there are tons of features with relatively large ranges) but it is still able to capture some important information about the underlying distributions if tuned correctly.\n",
    "\n",
    "We use a feature included with MWEM that allows a column to be specified for a custom bin count, if we are capping every other bin count at a small value. In this case, we specify that the numerical column (784) has 10 possible values. We do this with the dict {'784': 10}.\n",
    "\n",
    "Here we borrow from a scikit-learn example, and insert MWEM synthetic data into their training example/visualization, to understand the tradeoffs.\n",
    "\n",
    "https://scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html#sphx-glr-download-auto-examples-linear-model-plot-sparse-logistic-regression-mnist-py\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.datasets import fetch_openml\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.utils import check_random_state\n",
    "\n",
    "# pip install scikit-image\n",
    "from skimage import data, color\n",
    "from skimage.transform import rescale \n",
    "\n",
    "# Author: Arthur Mensch <arthur.mensch@m4x.org>\n",
    "# License: BSD 3 clause\n",
    "\n",
    "# Turn down for faster convergence\n",
    "t0 = time.time()\n",
    "train_samples = 5000\n",
    "\n",
    "# Load data from https://www.openml.org/d/554\n",
    "data = fetch_openml('mnist_784', version=1, return_X_y=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_np = np.hstack((data.data,np.reshape(data.target.to_numpy().astype(int), (-1, 1))))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from snsynth.mwem import MWEMSynthesizer\n",
    "\n",
    "# Here we set max bin count to be 10, so that we retain the numeric labels\n",
    "synth = MWEMSynthesizer(10.0, 40, 15, 10, split_factor=1, max_bin_count = 128, custom_bin_count={'784':10})\n",
    "synth.fit(data_np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_size = 2000\n",
    "synthetic = synth.sample(sample_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Trained on Real Data\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.81      0.88      0.84        40\n",
      "         1.0       0.83      1.00      0.91        53\n",
      "         2.0       0.73      0.50      0.59        32\n",
      "         3.0       0.75      0.71      0.73        38\n",
      "         4.0       0.67      0.83      0.74        42\n",
      "         5.0       0.65      0.65      0.65        40\n",
      "         6.0       0.85      0.80      0.82        35\n",
      "         7.0       0.70      0.57      0.63        40\n",
      "         8.0       0.66      0.63      0.64        30\n",
      "         9.0       0.65      0.62      0.63        50\n",
      "\n",
      "    accuracy                           0.73       400\n",
      "   macro avg       0.73      0.72      0.72       400\n",
      "weighted avg       0.73      0.73      0.73       400\n",
      "\n",
      "Accuracy real: 0.7325\n",
      "\n",
      "Trained on Synthetic Data\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.00      0.00      0.00        40\n",
      "         1.0       0.17      0.66      0.27        53\n",
      "         2.0       0.03      0.03      0.03        32\n",
      "         3.0       0.08      0.11      0.09        38\n",
      "         4.0       0.00      0.00      0.00        42\n",
      "         5.0       0.13      0.07      0.10        40\n",
      "         6.0       0.25      0.03      0.05        35\n",
      "         7.0       0.00      0.00      0.00        40\n",
      "         8.0       0.05      0.03      0.04        30\n",
      "         9.0       0.33      0.30      0.32        50\n",
      "\n",
      "    accuracy                           0.15       400\n",
      "   macro avg       0.10      0.12      0.09       400\n",
      "weighted avg       0.11      0.15      0.10       400\n",
      "\n",
      "Accuracy synthetic: 0.15\n",
      "\n",
      "Random Guessing\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.07      0.08      0.08        24\n",
      "           1       0.07      0.05      0.06        56\n",
      "           2       0.02      0.05      0.03        19\n",
      "           3       0.21      0.10      0.14        77\n",
      "           4       0.00      0.00      0.00         6\n",
      "           5       0.11      0.09      0.10        56\n",
      "           6       0.05      0.06      0.05        33\n",
      "           7       0.14      0.20      0.16        30\n",
      "           8       0.03      0.02      0.03        47\n",
      "           9       0.14      0.12      0.13        52\n",
      "\n",
      "    accuracy                           0.09       400\n",
      "   macro avg       0.08      0.08      0.08       400\n",
      "weighted avg       0.11      0.09      0.09       400\n",
      "\n",
      "Accuracy guessing: 0.085\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3UAAANeCAYAAAC1ZSfVAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd3xT5fcH8M+TriQdbJANMpShgoAILlTcICIquDfuPX7ugYuvOFBRFCfbBQ4UleFARJAhS1kiU9mze+X8/jiNbZN707RNM9rP+/XKC0hubp7cpOWee57nHCMiICIiIiIiotjkiPQAiIiIiIiIqOIY1BEREREREcUwBnVEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVERFQhxpgPjDFPR3oc5WWMEWNM20iPo7oyxvxojLkuhPvLMMYcGqr9ERFVRwzqiIiiSNEJrPfmMcZkl/j3pcaY2saY94wx240x6caYtcaYB0o8X4wxK4wxjhL3PW2M+aDo762KtsnwuQ22Gc+Pxpicom12G2OmGmMaV+B9lSuQKgoY84ped68xZqYx5vDyvm55lXi/6caYg8aYxcaYB4wxSeXYR9QFjcaYTsaYGUXHcn/R+zo7BPt9whgzIRRjLNqfX0AoIiki8neoXoOIqDpiUEdEFEWKTmBTRCQFwGYA/UvcNxHAywBSAHQAUAvAuQD+8tlNEwBDynip2iVfS0Q+CrDtrUXjaQ+gdtEYwuH5otdtCuAfAO+G6XVvFZFUAI0B3AM9ltONMSZMr18VpgGYCeAQAA0B3A7gYERHREREIcOgjogotvQAMElE9omIR0RWi8inPts8D+BJY0x8KF9YRPYCmAKgs9XjxpjrjTF/FWWDvjTGNCm6f07RJssCZQUDvG42gI8BdCnxWk2MMVOMMbuMMRuMMbeXeOwYY8yvRRmpbcaYUcaYxPK9W0BEMkXkR2jg3AvAOWXt3+q9GmPqGGO+KhrrvqK/N7N6TWPM/xljPvW57xVjzKtFf7/KGPN3USZxgzHm0rLehzGmPoDWAN4Wkbyi2y8iMrfo8ZXGmP4ltk8oysp2LZHZvdIYs7no/oeLtjsTwEMABhe912UlXralMeaXonHOKBqDd//HGmPmFR2/ZcaYPkX3PwPgBACjivY3quj+/zKfxhiXMeZFY8wmY8wBY8xcY4yrrGNARFTdMagjIoot8wE8Y4y52hjTzmabqdAszFWhfOGiE/NBAH63eOwUAM8BuAia4doE4EMAEJETizY7KoisoNXrJgO4GEUZSaNTS6cBWAbN4p0K4E5jzBlFTykEcBeA+tBg7FQAN5fnNUsSkc0AFkEDjoD7t3mvDgDvA2gJoAWAbACjbF7uQwBnG2NSi95rHPSYTio6Dq8COKsok9gbwNIg3sIe6LGbYIw5zxjTyOfxcQAuK/HvswFsE5GSn/PxAA4req+PGWM6iMi3AJ4F8FHRez2qxPaXALgamhVMBHBv0ftpCuBrAE8DqFt0/xRjTAMReRjAzyjKDIvIrRbv5QUA3Yree10A9wPwBHEMiIiqNQZ1RESx5TYAEwHcCuDPoszYWT7bCIBHATwaIEO1uyhT4r11CPCarxpj9kODqG0A7rbY5lIA74nIEhHJBfAggF7GmFZBvzN/9xa9bjo0qLi86P4eABqIyLCirNPfAN5G0ZRTEVksIvNFpEBENgJ4C8BJlRgHAPwLDSLKvX8R2SMiU0QkS0TSATxjt72IbAKwBMDAortOAZAlIvOL/u0B0NkY4xKRbSLyR1kDFxEBcDKAjQBeBLDNGDOnxEWBCdBAMq3o35cDGO+zmydFJFtElkG/B0chsPdFZK1FlvUyANNFZHpRpnkmNGAuc31fUTB/DYA7ROQfESkUkXlF3zciohqNQR0RUQwpOrF+VkS6AagHPWH+xBhT12e76QC2ArjBZlf1RaR2iduqAC97e9E2TUXkUhHZZbFNE2h2zvv6GdAMUdNyvD1fL4hIbQCtoNmtw4rubwmgScmgFDoNsBEAGGPaF01x3G6MOQjNJtX33Xk5NQWwtyL7N8a4jTFvFU0ZPAhgDoDaRVk4K5OgmUlAM16TAJ0OCmAwgBuhgdnXJsjiMSKyVURuFZE20OOXCc3QQUT+BfALgEHGmNoAzoJeOChpe4m/Z0HXdQZit31LABf6fHbHQ7O7ZakPwAlgfRDbEhHVKAzqiIhilIh4A4pk6JopXw9Dgx13GIbzL/SEHcB/UybrQQucVErR9Mc7ALxStH5qC4ANPkFpqoh4sz2jAawG0E5E0qDHoMJFTowxzaFT/n6u4P7vgQakPYu2907RtHvOJwD6FK27G4iioA4AROQ7ETkNGgSthmYoy0VEtgB4HaXXRo6FZtEuBPCriAT7uUk5X34LgPE+n12yiAwPYn+7AeQAaFPO1yQiqvYY1BERxRBjzKPGmB7GmERjjBMa7OwHsMZ326IiHysBXBmGoU0GcLUxpovR8v/PAlhQND0RAHYAKNVrrKgARp9gdl40Te9fAEMB/AYgvaioiMsYE2eM6WyM6VG0eSp0TWFGUSbrpoq8oaIM20kAvih6zelB7t/3vaZCM437izKqj5fxXncB+BG6Dm+DN4tqjGlkjBlQFDDnAshAEOvJjBZqedIY09YY4yhaG3kNdH2m1+cAjoZ+n8aVtc8SdgBoZUq00CjDBAD9jTFnFH1uTmOMN4D17s+yJ52IeAC8B+Alo4Vy4owxvUw52k0QEVVXDOqIiGKLQE/2d0ODnNMAnFM03dHKIyhaC+Zjvyndp85qnVzwgxKZBV3HNwW67q4NSrdVeALA2KIpdxcVZb/SAawox8uMgBbGiAfQD7pOawP0WLwDbfEAaPGNS4r2/zaAchVmgVZfTIcGGCOL3tOZRUFFMPt/AiXea9E+XEXjnA/g2yDGMAlAX5TI0kH/z74b+rnvha7LuwkAjDEnGGPsvgN50Cmss6DB6EpoUHiVd4OitW9ToBnfqUGMz+uToj/3GGOWlLVxUZZwADS7uQuaubsPxecjrwC4wGiV0FctdnEv9DuzEHoM/geeyxARwej6aSIiovAxxlwGoJOIPBjpsZAyxjwGoL2IXFbmxkREFFUY1BEREdVwRdNCfwdwuYjMKWt7IiKKLpyyQEREVIMZY66HToP8hgEdEVFsYqaOiIiIiIgohjFTR0REREREFMPiIz2AYNWvX19atWoV6WEQERERERFFxOLFi3eLSAPf+2MmqGvVqhUWLVoU6WEQERERERFFhDFmk9X9nH5JREREREQUwxjUERERERERxTAGdURERERERDEsZtbUERERERFRdMrPz8fWrVuRk5MT6aFUC06nE82aNUNCQkJQ2zOoIyIiIiKiStm6dStSU1PRqlUrGGMiPZyYJiLYs2cPtm7ditatWwf1HE6/JCIiIiKiSsnJyUG9evUY0IWAMQb16tUrV9aTQR0REREREVUaA7rQKe+xZFBHREREREQUwxjUERERERFRzIuLi0OXLl3QuXNn9O/fH/v376/Qfj744APceuutlvc3aNAAXbt2Rbt27XDGGWdg3rx5Ze7v888/x59//lmhsQSLQR0REREREYWPCPDZZ8BZZwEnnwy8+y6Qn1/p3bpcLixduhQrV65E3bp18frrr4dgsKUNHjwYv//+O9atW4cHHngA559/PlatWhXwOQzqiIiIiIioern5ZuDyy4FvvwV+/BG44w7gjDOAwsKQvUSvXr3wzz//AADWr1+PM888E926dcMJJ5yA1atXAwCmTZuGnj17omvXrujbty927NhRrtc4+eSTMXToUIwZMwYA8Pbbb6NHjx446qijMGjQIGRlZWHevHn48ssvcd9996FLly5Yv3695XaVxaCOiIiIiIjCY80aYOxYIDOz+L7MTGDhQg3yQqCwsBCzZ8/GueeeCwAYOnQoXnvtNSxevBgvvPACbr75ZgDA8ccfj/nz5+P333/HkCFD8Pzzz5f7tY4++uj/gsTzzz8fCxcuxLJly9ChQwe8++676N27N84991yMGDECS5cuRZs2bSy3qyz2qSMiIiIiovD44Qfr+zMygG++Ac45p8K7zs7ORpcuXfDPP/+gQ4cOOO2005CRkYF58+bhwgsv/G+73NxcANpbb/Dgwdi2bRvy8vKC7glXkoj89/eVK1fikUcewf79+5GRkYEzzjjD8jnBblcezNQREREREVF41KsHxFvklRITgUaNKrVr75q6TZs2QUTw+uuvw+PxoHbt2li6dOl/N+8auNtuuw233norVqxYgbfeeqtcfeG8fv/9d3To0AEAcNVVV2HUqFFYsWIFHn/8cdv9BbtdeTCoIyIiIiKi8OjXD4iL878/Ph644oqQvITb7carr76KF198EW63G61bt8Ynn3wCQDNry5YtAwAcOHAATZs2BQCMHTu23K/z008/YcyYMbj++usBAOnp6WjcuDHy8/MxceLE/7ZLTU1Fenr6f/+2264yGNQREREREVF4uFzArFlA48ZAaiqQlqa3Dz8EWrYM2ct07doVRx55JCZPnoyJEyfi3XffxVFHHYVOnTrhiy++AAA88cQTuPDCC9GtWzfUr18/qP1+9NFH6NKlC9q3b49nn30WU6ZM+S9T99RTT6Fnz5447rjjcPjhh//3nCFDhmDEiBHo2rUr1q9fb7tdZZiS80CjWffu3WXRokWRHgYREREREflYtWrVf8FNUDweLY6Slwf07KnTL6kUq2NqjFksIt19t2WhFCIiIiIiCi+HQ4M5CglOvyQiIiIiIophDOqIiIiIiKjSYmVZVywo77FkUEdERERERJXidDqxZ88eBnYhICLYs2cPnE5n0M/hmjoiIiIiIqqUZs2aYevWrdi1a1ekh1ItOJ1ONGvWLOjtGdQREREREVGlJCQkoHXr1pEeRo3F6ZdEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVERDVEQQHg8UR6FERERBRqDOqIiKq5VauAE08EnE69XXIJsG9fpEdFREREoRKSoM4Y854xZqcxZmWJ+54wxvxjjFladDu7xGMPGmP+MsasMcacEYoxEBGRv927gd69gblzgcJCID8fmDIF6NsXEIn06IiIiCgUQpWp+wDAmRb3vywiXYpu0wHAGNMRwBAAnYqe84YxJi5E4yAiohLefx/IzS0dwOXlAWvXAr/+GrlxERERUeiEJKgTkTkA9ga5+QAAH4pIrohsAPAXgGNCMQ4iIiptxQogO9v/fhEN7IiIiCj2VfWauluNMcuLpmfWKbqvKYAtJbbZWnSfH2PMUGPMImPMol27dlXxUImIqp8ePQC32/9+EeCII8I/HiIiIgq9qgzqRgNoA6ALgG0AXizvDkRkjIh0F5HuDRo0CPHwiIiqvyuuAFJSAEeJ3/ZOJ9C9O9CtW+TGRURERKFTZUGdiOwQkUIR8QB4G8VTLP8B0LzEps2K7iMiohCrVQtYuBA47zzA5QJq1wZuuAH45ptIj4yIiIhCJb6qdmyMaSwi24r+ORCAtzLmlwAmGWNeAtAEQDsAv1XVOIiIaroWLbTiJREREVVPIQnqjDGTAfQBUN8YsxXA4wD6GGO6ABAAGwHcAAAi8ocx5mMAfwIoAHCLiBSGYhxEREREREQ1jZEYaVTUvXt3WbRoUaSHQUREREREFBHGmMUi0t33/qqufklERERERERViEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVEREREREQxjEEdERERERFRDGNQR0REREREFMMY1BEREREREcUwBnVEREREREQxjEEdERERERFRDIuP9ACIiIiIqHJEgJ9+Aj79FEhMBC6/HOjaNdKjIqJwYVBHREREFMNEgKFDgcmTgawswBjgzTeBxx8H/u//Ij06IgoHTr8kIiIiimHz5mlAl5mpAZ7HA2RnA088AWzZEunREVE4MKgjIiIiimFTp2qGzpfDAUyfHv7xEFH4MagjIiIiimEuFxAX53+/wwE4neEfDxGFH4M6IiIiohh26aVAQoL//R4PMGBA+MdDROHHoI6IiIgohnXoALzwgmblUlKA1FTA7QY++gioXTvSoyOicGD1SyIiIqIYd/PNwKBBwLffatbunHOAWrUiPSoiChcGdURERETVQKNGwJVXRnoURBQJnH5JREREREQUw5ipIyIUFgLz5wP5+UCvXkBSUqRHRERERETBYlBHVMPNnw+cey6QkwMYo/dNnAj06xfZcRERERFRcBjUEdVgmZnAmWcCBw6Uvn/wYGD1aqB588iMi4iqnz17dDbAIYdEeiRERNUP19QR1WBffKF9jHwVFgLjx4d/PERU/WzZApxwAtCkCdCqFdCxI7B4caRHRURUvTBTR1SD7dunV8595eYCu3eHfzxEVL0UFmpAt3Wr/h0AVq0CTj4ZWL8eaNAgsuMjIqoumKkjqsFOOaV4HV1JKSk6LZOIqDJmzAD27i0O6LwKCoAPPojIkIiIqiUGdUQ1WIcOwBVXAMnJxfclJwPHHQf07Ru5cRFR9bB5swZwvrKzgb/+Cv94iIiqK06/JKrhRo/WrNw77wB5ecDllwMXXww4eMmHiCqpe3f72QDHHx/+8RARVVdGRCI9hqB0795dFi1aFOlhEBERUTmcdRbw00+anQOAxESgZUtg+XLA6Yzs2IiIYo0xZrGIdPe9n9fiiYiIqMp88QXw6KNA69ZA06bAzTcDCxYwoCMiCiVm6oiIiIiIiGIAM3VERERERETVEIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiIiIKIYxqCMiIiIiIophDOqIiIiIiIhiGIM6IiIiIiKiGMagjoiIiCgIOTlAXl6kR0FE5I9BHREREVEAa9cCJ5wApKTo7dxzgR07Ij0qIqJi8ZEeABEREVG0OnAA6NUL2LcPEAEKC4FvvtEgb9UqIC4u0iMkImKmjoiIiMjWhAk67VKk+L6CAmD7dmDWrMiNi4ioJAZ1RERERDZWrQKysvzvz88H/vor/OMhIrLCoI6IiIjIRvfuuo7OV3w8cOSR4R8PEZEVBnVERERENgYPBurW1SDOKykJ6NQJOP74yI2LiKgkBnVERERENlwu4LffgIsvBtLSgHr1gJtuAmbPBoyJ9OiIiBSrXxIREREF0KgRMG5cpEdBRGSPmToiIiIiIqIYxqCOiIiIiIgohjGoIyIiihJ79gALF+qfREREwWJQR0REFGGFhcCNNwJNmwJ9+wLNmgHXX69NromIiMrCoI6IiCjCnnkGGD8eyM0FDh4EcnKASZOAYcMiPTIiIooFDOqIiIgi7JVXgKys0vdlZQGvvRaZ8RARUWxhUEdERBRhBw7Y3y8S3rEQEVHsYVBHREQUYUcfbX1/165scE1ERGVjUEdERBRhr74KuN2Ao+h/ZYdD/83pl0REFAwGdURERBF27LHAb78BF18MdOoEDBkCLFgA9O4d6ZEREVEsiI/0AIiIiEiDuQkTIj0KIiKKRczUERERERERxTAGdURERERERDGMQR0REREREVEMY1BHREREREQUwxjUERERERERxTAGdURERERERDGMQR0REREREVEMY1BHREREREQUwxjUERERERERxTAGdURERERERDGMQR0RERGF1b//AnfeCXTpApx3HjBvXoQHREQU4+IjPQAiIiKqOTZvBrp2BdLTgfx8YNkyYOZM4J13gIsvjvToiIhiEzN1REREFDZPPgkcOKABnVdWFnDbbUBBQeTGRUQUyxjUERERUdjMmgUUFvrfn5MDbNwY9uEQEVULDOqIiIgobBo2tL6/oACoWze8YyEiqi4Y1BEREVHY3H8/4HaXvi8pCTjjDAZ1REQVxaCOiIiIwubCC4EHHwRcLiAtDXA6gZNOAsaPj/TIiIhilxGRSI8hKN27d5dFixZFehhEREQUAunpwJ9/Ak2aAM2bR3o0RESxwRizWES6+94fkkydMeY9Y8xOY8zKEvfVNcbMNMasK/qzTtH9xhjzqjHmL2PMcmPM0aEYAxEREcWO1FSgZ08GdEREoRCq6ZcfADjT574HAMwWkXYAZhf9GwDOAtCu6DYUwOgQjYGIiIiIiKjGCUlQJyJzAOz1uXsAgLFFfx8L4LwS948TNR9AbWNM41CMg4iIiIiIqKapykIpjURkW9HftwNoVPT3pgC2lNhua9F9fowxQ40xi4wxi3bt2lV1IyWiqJaRATz+OHDYYcCRRwKjRrFJMREREZFXfDheRETEGFPuiiwiMgbAGEALpYR8YEQU9fLygN69gXXrtDkxAPzf/wHffw9MnRrZsRERERFFg6rM1O3wTqss+nNn0f3/ACi5LLpZ0X1ERH4++wzYsKE4oAOArCzgu++AZcsiNy4iIiKiaFGVQd2XAK4s+vuVAL4ocf8VRVUwjwVwoMQ0TSKiUn78Uadf+hIBfv017MMhIiIiijohmX5pjJkMoA+A+saYrQAeBzAcwMfGmGsBbAJwUdHm0wGcDeAvAFkArg7FGIioemrZUpsTl8zUAUB8PNDUcjUuERERUc3C5uNEFNW2bwfatSudrXM4gEaNgE2bgISEyI2NiIiIKJyqtPk4EVFVOeQQXT/XogXgdmvW7sgjgTlzGNARERERAWGqfklEVBm9ewMbNwLr1wNJSUDz5mU+hYiIiKjGYFBHRDHBGKBt20iPgoiIypKfD2zdCtSrB6SlRXo0RDUDp18SERERUUi8+y7QsCHQubP+efnlQHZ2pEdFVP0xU0dERERElfbtt8Dtt2svUa9PPwU8HmDixMiNi6gmYKaOiIiIiCrt2WdLB3SAtqOZMgXYty8yYyKqKRjUEREREVGlbd5sfX9CArBzZ3jHQlTTMKgjIiIioko7/nggLs7/fmOAVq3CPhyiGoVBHRERERFV2uOPaz9RR4mzS7cbeO45bUdDRFWHQR0RERERVVq7dsCiRcDgwUDTpsAxxwCTJgG33BLpkRFVf6x+SUREREQh0b69BnJEFF7M1BFFqYwMYMQIoGdP4MwzgenTIz0iIiIiIopGzNQRRaGsLJ22snFjcdPWuXOB++7TNQtERERERF7M1BFFobFjgU2bigM6AMjMBIYPB3btity4iIiIiCj6MKgjikLTpvk3cAWAxETg11/DPx4iIgq9HTuAYcOAQYOA//0P2LMn0iMioljF6ZdEUahJEy0J7fGUvt/jAerXj8yYiIgodFauBI47DsjLA3JygG++0XXUv/0GHHpopEdHRLGGmTqiKHTLLf49fRwOoGFDoFevyIyJiIhC54YbgIMHNaADdLr9vn3AXXdFdlxEFJsY1BFFoa5dgTFjgNRUIC0NSE4GDjsMmDULMCbSoyMiosooKADmz/e/3+MBZs4M/3iIKPZx+iVRlLrsMuCCC4AlS4BatYCOHRnQERFVBw4HEB+vUy99OZ3hHw8RxT5m6oiimNMJ9O4NdOrEgI6IqLpwOIAhQ/yn2TudwLXXRmZMRBTbGNQRERERhdlrrwHduun0+tRUwO0GTjgBeOqpSI+MiGIRp18SERERhVlaGvDLLzrFfs0aoHNn4IgjIj0qIopVDOqIiIiIIuToo/VGRFQZnH5JREREREQUwxjUERERERERxTAGdURERERERDGMQR0REREREVEMY1BHREREREQUwxjUERERERERxTAGdURERERERDGMQR0REREREVEMY1BHREREREQUwxjUERERERERxTAGdUREFJU2bgTuvRc44wzgsceAHTsiPSIiIqLoFB/pARAREflauBA45RQgNxfIzwfmzAFGjdL727SJ9OiIiIiiCzN1REQUdYYOBTIyNKADgJwc4MABzdwRERFRaQzqiIgoqmRnAytW+N/v8QAzZ4Z/PERERNGOQR0REUWVhAQg3mZxgDEa3BEREVExBnVERBRV4uOBwYOBxET/x3JygPvuC/+YiIiIohmDOiIiijqjRgG1a/vfX1AAvPGGrq8jIiIixaCOiIiiTmoqUKeO9WOJicCGDeEdDxERUTRjUEdERFGpY0ddQ+crLw9o0SL84yEiIopWDOqqIRFg8mTghBOAbt2AF14AsrIiPSoiovJ5+GHA5Sp9n9sNXHopULduZMZEREQUjRjUVUM33ghcfz0wdy6wZAnw2GPA8cfr1W0ioljRrRswbRpw+OGasUtOBm69FRg9OtIjIyIiii42RaMpVv31FzBunFaI88rOBtatA6ZMAS6+OHJjIyIqr1NOAVat0ibk8fHW0zGJiIhqOmbqqpm5c4G4OP/7MzKAGTPCPx4iolBISGBAR0REZIdBXTXTsKF1UJeYCDRpEv7xEBERERFR1WJQV82cdpoWFvC9oh0fD1x3XWTGREREREREVYdBXTWTkAD8+CPQtq0WFUhN1Spxn34KtG4d6dEREREREVGosVBKNXT44cCaNcDq1Vok5cgjNVNHRERERETVDzN11ZQxQIcOwNFHM6AjIgq73buBm24CGjXSTunDhgG5uZEeFRERVVM83SciIgqlrCygRw/gn3+0FwMADB8O/PIL8N13kR0bERFVS8zUERERhdKHHwK7dhUHdIDOhZ87F1iyJHLjIiKiaotBHRERUbBWrQKmTgX++MN+m19+ATIz/e8XYVBHRERVgkEdERFRWbKzgbPOArp1A66+GjjmGKBvX51q6cuuKWh2NvD000Dv3sC4cYDHU7VjJiKiGoNBHRERUVkeekj7xWRnAwcPajD3ww9AmzbAjTcCf/6p24kAn3xiv59Nm4BffwVuvhm46qpwjJyIiGoABnVERERlee89ICen9H0eD7B9O/DWW9o75oEHgAULtEBKWTIztYFooGmcREREQWL1SyIiorJkZwd+vLAQGDkSSEvTnjLBMEaLp3TqVOnhERFRzcZMHRERUVnatCl7m9xcYO3a0lUvA4mL0z52RERElcSgjoiIKJA9e4ANG4LbNjUVGDwYcLkCb2cM4HQCZ59d+fEREVGNx+mXREREgcycCSQmaiYuEKcTuOQSoGdPrY75+usaEB55pFbKfPFFncZZWKgVMr/4QvdLRERUSQzqiIiIAgkm8DIGuPxyoFcv/ffNN+utpHvuAVasAJKSgMMPD37tHRERURk4/ZKIiCiQM8/UVgWBOBzAt98CeXn228TFAV26AB06FAd0f/wBDByoxVKuugpYvTpUoyYiohqEQR0REVEgbjfw2WdAcrKumYu3mORSWAjs3w98+WXw+x05EujcGfj8c+1zN3YscPTR2haBiIioHBjUERERBbJ4sTYfz8rSXnUFBdbbZWYC69YFt8/Vq4G77/a/PzsbuP32io+ViIhqJK6pIyIisrNhA9CnD5CRof8O1K4gLg444oiy9zlrFjBggP2UzoULyz1MIiKq2ZipIyIisvPKK2VXvfRKSQHOOivwNhs2aECXlWW/TVntEIiIiHwwqCMiIrKzdGlwzcTj4nTa5OjRwNy59lm4MWPK3t+115Z7mEREVLNx+iUREZGdHj2AX3+1rmoZFwd4PNqfLj4eGDFCs3rGAO3aAT/+qFm31NTi52zaFDioO+ww4KWXQv42iIioemOmjoiIwmPXLuDGG4FGjYCWLYFnngncAiAa3HGHBm0le8q5XNrm4OGHtffcEUdokZSsLK2CWVAArFql77NePeDYY4tbFfTtq1U0rTz+uD7PqromERFRAEbK6r0TJbp37y6LFi2K9DCIiKi8Cgu1TP8FFwC7dxdnqlwu4JRTgK++iuz4yvLnnxrczZmj6+ZuvFEDsMREDeRq1bKviAloQFinjq6nS0gAunYFNm4sXquXnAxcdBHw3ntheTtERBS7jDGLRaS77/28HEhERFVn5kzgkkuAgwf9s3LZ2cAPPwDLlwNHHhmZ8QWjY0d9H1Y8Hr0FIqIB3OTJwA03aID74ovAxx9rkHjzzdp4nIjCIj9f20POnQu0aAFccQXQoEGkR0VUOQzqiIgotA4eBD76CFi5EnjrrcDVI43RPnDRHNQFkpICtGlTdn+6zEzgr7/077VqAcOG6Y2IwiojAzjuOODvv/XvLhfwxBPaaaRnz0iPjqjiGNQREVHorFgBnHiiXgrPzCx7e2OAVq2qfFhVatIkLagSSEoK0N1vtgwRhdmIEcDatUBOjv47O1v/vPhiYP360stniWIJC6UQEVHoDBkC7N8fXEAXHw80aQKcdFKVD6tKHX544DPBhASgcWNg4MDwjYmILE2eXBzQlbR9uy51JYpVDOqIiCg0/vlH5zQFq3174KefAEeM/1eUnKzVPK0kJADXXQfMn6+FVYgoohISrO8XsX+MKBbE+P+kREQUNRwO+6bbVrZvrx5znYwBXn9dF+d4ORwa7C1YALzxBlC3buTGR0T/GToUcLtL32eMJtybNYvMmIhCgUEdERGFRuPGZU9FLOnAAc1iVQdnnw3Mnq1/tmkDXHgh8Ntv2r6AiKLGzTdrJxW3W1tQpqYCDRtqMVqiWMY+dUREFDqrV2uhlJwcLS0X4P+Yv9Ea++Pro/O+uUhM4dREIgqfRYs0kd60qV6L4ezoqufxaJXRb7/VyQtXXKEtJah87PrUMagjIqLQys4GPvtM19eNGwf8+2+pwin/oAkG4Av8iY6IRwEcaal48y2DIUMiOGYiIqoyhYVA//7Azz/r9b7ERCAuTgvXDBgQ6dHFFgZ1REQUfvn5wBdfAA8/DKxbBxHBEViB1TgMhSiuSuB2ayNgzlYkAMjK0rLzhxyiNyKKbRMnAjfc4F8YOTUV2LlTp8JScOyCOq6pIyKiqpOQAFxwATBnDtC8OX53HYdNaFkqoAN0tuZrr0VojBRVXngBaNBAO120agWce65e2Sei2DVhgnWnG2OAX34J/3iqIwZ1RERU9Ro1AlavxvYbn4AjMd7vYY8H2Lw5AuOiqDJ1KvD445qpO3gQyM0FZswArroq0iMjosoItGaR6xlDg0EdERGFh8uFYx7qizyHy+ohnH12BMZEUeV//9OArqTcXOCrr4B9+yIzJiKqvOuu0y4vvhITgV69wj+e6ohBHRERhU39+sC995b+zz0pSddNVZfuBlRx27db3x8fD+zZE96xEFHo9OunGXeXS2+pqUBaGvDll/rzTZXHoI6IiMJq2DBg/HhdM3XEEcD//R+weLH+B08128kna0U8X4mJur6OiGKTMcCoUcCSJcCIEcCbb2phZGbpQofVL4mIiCgqbNyoFVAzMoCCAr3P7QZGj9aeVkRENR2rXxIREVFUa9UKWLZMp+J26ACccQbw9dcM6IiIysJZrERERBQ1WrTQzBwREQWPmToiIiIiIqIYxqCOiIiIiIgohnH6JRERlU9+PvDZZ9o8rFEjXQB12GGRHhUREVGNxaCOiIiCl5sL9OkDrFypJQrj44E33gA++AC48MJIj46IiKhG4vRLIiIK3gcfAMuXa0AHaN35rCzg2muBnJyIDo2IiKimYlBHRETByc4GRo7UIM6XMcCCBWEfEhERETGoIyKKetu3AzfeCDRurEvXPvgAEAnzIDZsAFq3Btats37c49Eu0Tb27QPeeQd46SVgxYoqGiMREVENZSTsZwYV0717d1m0aFGkh0FEFFZ79gDt2wN795a+f8gQYPLkMA6kRw8g0O/gxETgn3+A+vX9Hpo9GxgwQP+enw/ExQFXXqlL8YypovESERFVQ8aYxSLS3fd+ZuqIiKLYCy/4B3QA8OGHwF9/hWkQ33wTOKADNHV4zTV+d+dmezDofEFmJpCZCeTl6SzO8eOBb7+tovESERHVMAzqiIii2Kef2j/2+uthGsTtt5e9TX4+MH06sH+//jsrC7jhBvxU61zIwYN+m2dmAu+/H9phEhER1VQM6oiIolhKiv1jYZm6mJ6u6+mCUVgI3Habrq/r2RN4+20U5hfabl5QEKIxEhER1XAM6oiIophdkszhAC66KAwDcDrLFz1+/DFw5pnax04EffAjPBb/1SQnA1dcEcJxEhER1WAM6oiIothVVwHdupW+z+EAzjpLk2FV6vvvgfPOA1yu4J+TmAj8+ON//3QhB5NwCVzIQhKyYeBBcjLQvz9w7rkhHzEREVGNFB/pARARkT1jgPnzgbFjgTff1MqRp5yit7w8ICmpil549Gjg3nute9IFkpurUWcJ/fEV/kJbfGguxv6eZ+LMF09Dr16sfElERBQqbGlARBQj5swBBg4sXotmjFbBPPPMEL9QdjbQoIFWM/EVH6+ZO49Hi6Pk5RU/lpQEdOyoZTnT0/2fm5SkjzVrFuIBExER1QxsaUBEFMMOHADOOUfbGxw8qLcDB4BBg7Q5eciIAM8+q4GdlVatgK++0gZ6330HtG0LJCRowHbhhdqULjnZ+rm1a5dvKidRVfJ4tLei1cULIqIYw6COiCgGTJmi8ZavwsIQNyF/9FHgxRf1hNdKmzbAiSdqENenD7B2LbBzp0aY48cDdeoAP/2kGT1fu3YBDzwQwsGSnRiZhBM5U6YATZoA7doB9eoBl19e/qnGRERRhEEdEVEM2LdPl6v5ys0FVq8O0YscOKABnV2Wzu0G7rmn9H3GaAau5OK++HgtmOLL4wHefRdYtixEAyZfs2YBnTrp2su6dYGnn7aPz2usefO09OqOHfpdz83VhpCXXx7pkRERVRiDOiKiGNC3r2blrCxdGqIXWbPGvvKKMcDw4cBpp5W9n+Rk+8GKAHfcUfExkq3584EBA4A//9TDvG8f8NxzwP/9X6RHFmWee84/K5eTA0yfHuK5zERE4cOgjogoBhx2mP1jK1eG6EWaN9eTW1/GaA+C224Lbj+NGvn3YSjpl18qNj4K6Ikn/GOVrCzg9de5bKwUu0xxYqKusSMiikEM6oiIYoC3FomVtLQQvUjjxsDZZ2vD8ZJcLuDhh8u3r08+se9ZkJJSsfFRQKtWWd8fF8dY5T8rVwJbtlg/lp8f+OoJEVEUY1BHRBQD4uKAK6/0j7fc7uATaEGZMAG46CKNIJOSgKZNtRLLMceUbz9Nmug0S99I1OUCbrwxdOMNlx9/BAYPBs44A3jnHesFjhHWubP1/YWF7CLxn1tvtX9s0CBecCCimMXm40REMeLll4Ft24AZMzRWys3V+Cuka6bc7uJO5wcPAg0bVrxL+PDhwObNulbJO+B+/YAnnwzhgKvY1q3A+ecDixYVl5ScOxcYM0b/tCoIEyFPPqmxZ8kpmG63xtZud8SGFV3++MP+scaNwzcOIqIQY1BHRBQjXC7giy+ATZuA9euBDh2q8DzU5ap8T7mkJC0dv2mTtj447DCgRQt97MAB7abudmuLhISEyo85lA4cAF57DXjqqdIN1gGNmv78E/joo6iqmNi9O/DNN8CddwLLlwP16wP33QfcfXekRxZF2rQBdu+2fuy448I7FiKiEDISI81sunfvLosWLYr0MIiIqLLee0+nwXkDucRE4Ouvyz/FsyoUFgK//w6cdRawfz9QUGC/7cCBwNSpYRsahcD8+UCvXv73166t5UKJiKKcMWaxiHT3vZ9r6oiIKHxWrtSALjtbp3cePKiZkzPPjPw6tTff1OmmPXvqmAIFdMYADRqEb2wUGsceq+tGS85HbdvWvsoMEVGMYFBHRETh8+67/tMZAc2Qffdd+Mfj9dFH2lh9797gunUnJQE33FD146LQu/RSICNDF6gePAisWwccckikR0VEVClVvqbOGLMRQDqAQgAFItLdGFMXwEcAWgHYCOAiEeG8ByKiaLF4sa6HS0jQqo8dO4Zmv/v2WTcm93j0BDtSrJq82XE4gFdeAY4+ukqHRFXIGAZyRFSthCtTd7KIdCkx//MBALNFpB2A2UX/JiKiaHDffVq85H//A559VitwvPRSxfe3ezcwb55mRgYMAJKT/bfJzwdOOaXir1FZW7eWvY0xuu5v40Zg6NAqHxIREVGwIjX9cgCAsUV/HwvgvAiNg4iISlqyBHjjDc1aeTy6riw7W5uPb95cvn15PMDNNwPNm2tT80MP1Z53PXsWB3bG6Pqmhx/W3naRcsQR9o8lJ2sTuPXrgQUL9P0QERFFkXAEdQJghjFmsTHGe2mzkYhsK/r7dgCNrJ5ojBlqjFlkjFm0a9euMAyViKiGmzoVyMnxv98Y4KuvyrevF1/Unnc5OdoiICdH93H44drAe8AAXd/0zTfAo4+GZvwV9fzz/s3ckpKAa6/VtX7LlwOtW0dmbBQeBw/qtOOdOyM9EiKicgtHn7rjReQfY0xDADONMatLPigiYoyx7KsgImMAjAG0pUHVD5WIqIaLj9c1Y77FQgoLgysgUtLIkf7r1LKzgfffB159FRgypFJDDanjjwdmzgQeeEArdLZsCQwbBvTvH+mRUVUT0Q7tb7xR/B0/9lhg9uzK92okIgqTKs/Uicg/RX/uBPAZgGMA7DDGNAaAoj95WYyIKBoMGWLdCDwvD3j9dSAzM/h92fX9ysuzroAZab17a0P0vXu1Vx0DuprhxRe10XxhoQZ4IsCvvwInnBDpkRERBa1KgzpjTLIxJtX7dwCnA1gJ4EsAVxZtdiWAL6pyHEREFKTDD9cMlZVNm4C33gp+X8cdZ31/+/bMgFD0eOYZ6/sXLwZ27AjvWIiIKqiqM3WNAMw1xiwD8BuAr0XkWwDDAZxmjFkHoG/Rv4mIKBr06gWkpPjfn50NfPxx8Pt56SXdT3zRTH+HQ9etvfFGaMZZA61bBwwfDjz3HLBmTaRHU02kp9s/tmhR+MZBRFQJVRrUicjfInJU0a2TiDxTdP8eETlVRNqJSF8R2VuV4yAionJIS9MpaFYWLgz+RLdTJy39HxenhVZq1wbGjQP69AnVSGuUl14CjjwSeOwxvXXtqgEeVVLDhtb3G6OZayKiGBCplgZERBStOncGmja1fszj0bVn2dnWj2dna8+3ggJg0CCNRHJzNUjcuxe48EINDKlc/v5buz7k5GhLP2+niWHDgLVrIz26GGfXg7FTJ6BNm/COhYioghjUERFRacYAX3+tJf2t5OeXThEVFAA//KBBXL16wGGH6Z+ff+7/XBHgssuqZNjV2eefWxcfzcsDpkwJ+3CqlyFDtFJrUpJ+9x0OnYI8Z06kRxYxS5fqLOmpU6OzphER+QtHSwMiIoo1bdvq7Y8/rB/3nvAuWKBVIg8cCP7sb9260IyxBjFGb74KC7Wf+wMPWD9OQbrjDuCWWzQlWqcO0KBBpEcUEYWFwEUXAd9+qxcREhK0ptFPP3EmKlG0Y6aOiIis9e1r/1jnztqD7owzgF27ync536plAgV0/vn2j61Zoy32qJLi47Uyaw0N6ADg7bc1oMvK0qm+6en64x3o+0dE0YFBHRERWXv2WesALDFRsxrTppW/ITkAXHIJtm/X7ghvvKFL8Ciwli11OaKVvDzgiSfCOhyqpsaM0YCuJBFg40Zg/fqIDImIgsSgjoiIrLnd2qurUSOtYJmQACQnAxMn6lysfft0vlYg8SVm+RsDdO+Occe9hdatgbvvBu69F2jXDnj11eLNMjKATz4BJk0Cdu+umrcWi/r3t09yLligx42oMuwS7g4H19YRRTsjdmWro0z37t1lEfvFEFF1sns3MH++Llg5eBA4+2ygXz8NoKKJCLBypUYN3bpppg7QtXFHHqnztHwZo4tx5szRx1euBI4/HtvqdsKhh/o/xekEli0DNmzQeiuOokuO+flaw+KGG6r0HcaEjAygVi375OjEicAll4R3TFS9DB+uFVV9i9s2awZs3sx1m0TRwBizWES6+93PoI6IKMxycoBrr9V0VH5+8f3JyUCPHsCMGbGz7uy224D33wcyM/XfDocGpaeeqtM3u3Yttfkbb2h2zvekMT5ei3288IJ/wOdyAUuWsFADABx3HDBvnvVjRx+tiVWiisrKAk44QdtkZGToxZa4OF1nd/zxkR4dEQH2QR2nXxIRhVpuLnDffdpsOyEBOOWU4iqSWVnAjTdqrfCSAR2ggdHChZpyiRWvvgp8+CEwYIAWTfngA32P33zjF9ABOlvT6lqiiD7VKumXnw9MmBDykcek556zf2zZMuvjRxQst1un8n7wgV6vGTYM+OsvBnREsYCZOiKiUDv9dGD27NLz5JKTdariwoXa1y2Qvn2rbTnDjRuBDh38g4/ERD1cdofmzjuBl1+u6tHFhpSU4sRoSQkJen8ok7wHDmhv7k8/BVJTgVtvBS69lNPwypSXpxduZs0CmjfXzHyzZpEeFRFVA3aZOvapIyIKpaVLrQOyzEzg11+D24fbHdIhRZNWrYCnngIee0wzcCLa87lePWDLFuvnOJ3AeeeFc5TRbehQYPTo0oFxQgJwzjmhDeiysoBjjtG1VN7XWrlSp3++8UboXqfayczUebLr1+scxqQkYMQI4MsvNWtPRFQFOP2SiCiURo+u3POTk/WsvRq7915d+/Xww8CDDwK//KLJDDt9+gAnnhi24UW9p5/WejXJyRr/p6YCbdpoOfpQmjBB202UDB4zM3UJ5aZNoX2tamPjRp2K7C0sBOh07MxMTXFWpAUIEVEQmKkjIgqlytTgT0wErr9eq2BWcx06lO6tdvnlmuT07ZEFaIGUvDxNeJAGcj//rGufli3TlhB9+hRXDA2VGTOsP4+EBC3a2rJlaF8vpuXnA1deqetL7Za1pKcDq1YBnTqFd2xEVCMwqCMiCqUTTgA+/zz4K/KHHKJRy2mnAUOGAIceWqXDi1bXXAN89BHw22/+gcTo0ZoA+eyziAwtKhkDHHus3qpKixZaldR3nWNeHtCwYdW9bkwaOBD4+uvA23g8OpeYiKgKsFAKEVEo7dsHtG2rf5b1+zUpSfvTefu+1XAeD3DhhdYxscOhbQ2OOioiQ6uR1q7VAqZW2Tq3WzOr7dqFfVjRw+MBXnlF18tt2xZ4W2OAjh11WiYRUSWwpQERUTjUqaPz4vr21QZPiYka5Pk2FI+L05KCDOj+43BoLGyV5PR4gJtvrvxr7NgBnH++xtNOJzB4sFZ4JH/t2+v6OStZWdrBoka75RbgkUfKDuji44FGjZhqJqIqxaCOiCjU2rbVBUmvvqpX6Lds0T+N0Xr0p52m1UH69YvcGHNytBLGvfcC775bXNQhwo4+2v6xhQsrN8ycHF3O9NlnOoUwNxf4+GMNXli/orTPP9cOHFddZb/N5s3A33+Ha0RRZseO4p6MgcTFAY8/rgerRqc1iaiqMagjIqoKmzcD99yjkUNuri5MEtHu26+9BvTsGbmx7dih6/huugl48UXgjju0fOKGDZEbU5Hbb7fvgSaimbyK+uADYM8e//t37qx80dLqZPx4LdS4YgWQnW2/nTH6ebzzjhZ8vPFGLdxSI/z5Z3CVe665Rsu8hrLXBBGRBQZ1REShlJmpteUvvFCDOV/5+cCUKeEfV0l336216r1pr8xMYNcurbwZYS1a2Bf/LCwErruu4lm1L7+0f+zjjyu2z0AN02ORCHD//WUnoABNOl91lV4T+PJL4K23gC5dgOOP169Xtda6taZ7rRij0y0/+UR/F7BTOxGFAYM6IqJQ8WbA7r5byzhaFUoRifxcv88+0wipyFq0wyUyAa1nv4M+J3kwa1YExwZtbF2rlv/9Itr4evbsiu23SRP7x6xeL5D9+4HLLgNcLk3Y9OkDrF5dsXFFk8zM4LpyxMfresT16/0DwF9+0T568+YB339fuexq1GrVSj9032qWbjcwZw6wfTtwwQWRGBkR1VAM6oiIQuWBB/RkLjPTfhsRYNCg8I2phMJCYPp04LGcBzEG1+MA0rAKh6M7FuEjXISNaIWf5jgwYIBOwYuUFi105qpvbRlAk4sVDeoefdT6fmM0OxUsEeDkk7UlWV6exug//QT07m09vTOWuN16s5KWpsHajTdqMLdsmf30zF27NOY5/3wNpp98ssqGHDmffKKRbVKSTq9s2xb46itNVRIRhRmDOiKiUPnii7Ln4iUlaeftMMvK0qBj8GDgKXkEd+EltMRG3IrXkIFkeEq0Lc3K0mRjiWRe2LVqpVkwX04n0KBBxfbZsiXw/POlm3THxQFDh5bvPHzWLA1ofI9PZqZ9tcjy2rIFeOkl4LnnwlsF3+HQANc3sHO7dSbhokW6/rBFC6B2bfv9iOhM4wMHtEDNiBFafKVaSU7WhZoHD2oUu3atRvtERBHAoI6IKFSCKZyQm6vFScLsxReB5cu9y+gMspCCA6iFn9AHAv+UWGYm8O+/YR/mfwYOtM7UORxaxKOi7rtPs0zDhwNPPKFByptvlm8fr71mPbM2Ly80hULGjwcOOwx46CHgsceAY44pXyaxsh58UJPOqanacaN+feDll/WCQEm33hp8L+3MTA1Sq6XERJ2/y7VzRBRBbD5ORBQqDz2kZ785OYG3S03VhUth7FHXvj2wbp3//QYeiMX1PadTh5icHIbB2fjtN+C884rruSQm6pTHvn0jN6YxY7RoqN2yyIceAp55puL7370baN7c/yvkduv6tHAWTS0oANLTNV5x2FwCfuQR4NlnrYNcX4cfDqxaVfo+Ec18fv01ULcucPnlWoOEiIissfk4EVFVe+wxneOYnBw4GvJ4ym5YHGJ2SYR4FMCJ0pUuXC7g4osjG9ABmqHaulWDmRkzdLliJAO6jz8G7rorcJ2biy/WavcXX6xdIs46SwuGBGv6dC1C4isnB5g8ufxjroz4eKBOHfuADgCefhr44w/9rOLjdWmZ1faJiUD//qXvKyzUVggDBgCvvAI89RTQsaMuVSMiovJhUEdEFCpOp1bx+PFHPUvt1Ml6O4+n9MKwggJNVTzyCDByZJXMe7z6av81asYIDju0AM8+lovUVC1Rn5SkRfveeCPAznbvLj4LX7s25GMtyeEAuncHjj3WOtgJp8cfD1zqv2NH/SiPOUYDwL//Br79VnvNT5tWudeOdMHUQDp0ABYs0PVz27cD48ZpZtF7IcG7DvK++0o/76OPNIj1FlspKNDg9aqrAtcaIiIif5x+SURUVWbN0jREyUjA7dZ+cCNH6r83bwaOO04DOe+Zu8OBpec9jomtH0VevsGFF+omlVmyk5sLnHEGsHixnjg7nRrA/fyznpTn5gIbN2p7rUAFMDBhAnDllcVjNQa45BK9v5pLTS2eCuqrSRM9ljfcAMuWEC1a6PEt6zPcswdo3FiLjPi67jrg7bfLPeyI+O03nYm8eTNw5pnALbfo9MqSOnSwbgMRF6dB8FlnhWesRESxxG76JYM6IqKq5J2zt2uXzkG7+WZdhORNO51wAjB3bqmnDMf9GIbHkWucEDjgdutao9GjKzcUEW2hNX8+0KyZlpu3qjBp6+BBnY9nlTaaPBkYMqRyA4xyxx6rGSlfdeoAO3fqR1qrlh4mXwkJ+hUIph9e06bWydrERL0+YFVAJha53fYtEaZNA/r1C+94iIhiAYM6IqJIEdEz/eTk0nMI9+3T1FiJtMwmtMDhWI0clI623G6d2XnsseEatIUXXvCfQ+fVuTOwYkV4x1PF/vpLC4V07qxB2Zw5mj3yTbyOHg1ccYX+u00bnXbpy+XS6YkJCWW/bkqK/fTDOXP0OkCw1q0DZs7UHnMDBmi2MVoEynxu364/GkREVBoLpRARRYoxmqLxXRRm0dNuOs6GgX8mLDsb+OyzqhpgkHbssH9s377wjaOKbdwIHHmk3k46SYOLL74ATjxR18j17q0f55FHAhMnFgd0gLYC8O3x5nLp1MlgAjoAaNjQ/rFge72JaAP3I48E7r1XK3Y2bapBYbSwy1rGxQU+BkRE5I9BHRFRpDRoALRrV+quJOTCYRHUxcUF3xOsypSMXnydfnr4xlGFPB7glFO0omN2tmbq9u3TZYOrV2uW7JdfgP37tSfdeeeVfv5112ky0+3WTJTTqZUwX3gh+DEMGmT/2LhxwRVNmTULeOstXT+Zna0ZsfR0zdbl5QU/lqp04ID1/cbo8SUiouAxqCOi2JWdDYwdq2fS//ufLmyKNRMnlkrtDMAX8Fg0A4+P18Aioo44QlNXvpxO4Pnnwz+eKjB3rhb39A2c8vKCW9NojDY137kT+PVXXRv37rvla0l4zz326+aysrS9QyAej/bKs5rC6fEAP/0U/Fiqkl02Lj4+8u00iIhiDYM6IopNe/dqkHHLLXrW/MQTQNu2QKytve3SRUsEPvAA0LEj6nVohEkXfAa3S5CSouurnE7gpZeAww6r+uFMmKDJQ7dbWwl8/73PBt9/r8e6Xj098+7fXxef1a9f9YMLA7sZpgUF+jEFKzlZO1rUqVP+MRxyiFaMtJKfD6xcaf/cwkKgW7fAgVu0ZOruv996qupVV5UvCCYiIhZKIaJYdccdwJtv+p+hduig3Z9j3P79wFdf6Un82WeHp2jE6NG6/qpkIRCXC/jmG+sEXXW0dasGtTk5pe9PTtbAeujQ8Ixj7FgtlOrbFy81VZO7vo28va69FnjvPfv9ut2aRYyGTJiItmZ8+WVdb5iXpxVZ33tP220QEZE/Vr8kourFru57UhKwaRNL55XknYcX4Ezek1+IBnULsTfDP0XSqxcwb15VDS763HWX9oPzHjanE2jZEliyxD+zVFWysrSS5q5dmn0DNPBp3hxYs8a6EXthoQbhVj3uAM1+jR8PXHRR1Y27ItLTNdnbrJkuMw0Vjwd49VVtCZmZqZVLn3lGjyERUaxi9Usiql58UxheHg/nbnlt2gScfLJ2E69dW8s3rl/vv53Hg/1nX4KMDOuLfH/8UaWjjDovvaTZohNOAI46Cnj4YW2mHa6ADtDXWrBA68/ExWkQ17+/BtdWAR2gM5K9AaCVt9+OvoAO0Oxj166hDegA4JxzgLvv1h+D3bs1oO3aVf8eMTk52ihy7doIDoJqoj17gKlTtcWJ3YUfim0M6ogo9uzaZd/gqnXrii1kqi7WrgUuvVRTS23b6uKqggK9/fKL1uP3DYinTUPar98hCbmWu2zdOgzjLrJ7t1aLdDo1Nh840DohW5WM0eBnzhxg6VKdIpiWFt4xAECLFsD06TotMTcXmDIlcAK6Th37aYtxcdW+N3wps2dr+wnfyUh79wJvvBGZMeG99zRyPf107TVx+OHAli0RGgzVJK+8opnwq6/W6rpNmgCLF0d6VBRqDOqIqGqJ6JXpCROA5ctDs8+5c3WemZVWrULzGrFo1SqtbjJ5slb1KCgofVbr8WhA9+mnpZ83dSriMw/gfjwPN0oHy+7EAjz1VBjGDmDDBs2MffqpBjH5+cC0aUDPnv5r3GoSh0NvZYmP13o7Vv3wnnuu7AR2QYFm83r10ttbb1m2UgyosFB7+t17r66V27WrfM8Plf/9z/p+EQ32wu7XX4HbbivuLZGbq/NoDz1U08BEVWThQuChh/R36MGD+vXbvVuLMTFjV73YTOIgIgqBffuAvn2Lpxp5PMDxx+tZX2Wartll4hyOmh3UPfyw/o8dSEaGFpjZvRu47DKtK5+WBsTF4eHCZxCPfPwPDyAdqTjE7MCI27ahf3+/qfshtX070K8f8Pvv/q0ECgu1aMyUKZqArOm+/Vanh+7cqcfsrru0EKnXo49qUDd8uH4V6tTR4CpQi0FAg53zzgN++KE4kbt8uTY7nz5ds5dlyc4G+vTROkUZGXrd5bHHtAVDr14VfMMVFGiKZaineQbllVesp4wXFOjvxK+/1m7se/YAxx4beLZBbq7+rgu2mz3VaG+/bX1RLDdXf96rSYtRAjN1RFSVbrhB669nZOgtK0u7It9+e+X2e8IJuhDH90zT6dTXrKl++SW47X79VS/dNmmi0zSXLwfi42EAPIDnsRd1kY5UbEnthIuf7lylQ164UIeweLF9U+2MjJq3rs/KCy/o1KmZM7Xx+QsvaEeMvXuLtzEGePBBDYSzszW4KSugA/Sr8+OPpeOOrCzg5591GmowXn0VWLGieGa0t+n54MH+0yCr2hln2Aei//d/4R0LgMBziPPz9cz6+ON1jmyTJtapxl9/1ce8c5O7dInN3pwUVvv22f9uLesaIMUWBnVEVDXy8/Uyv2/LAY8HeOcdnXpUESIaATz0kDb0SknRTJPbrWeVRx9d6aHHrMaNg982N1fTYJs361l7btF6uoQEGKcTrlpJMN9Mr1xGtQwieg5bVt+0lBTt+RZrRIBJkzRL1bGjZtH276/Yvg4e1KxXyaArN1eDtlGj/Lc3RtfXBZNhA/QrYHU1Pysr+KBu/HgN5Hzt2VPxH/eKuuMOTXyVZAxw7rm6rDTs+vWz7yjvlZ+vH3RODjBsmF4A89qyRYO+bduK71u2DGjfPvwRM8WUQYOsCx/n52tmnaoPBnVEVDUKC+1L8YnoGWp5bd6sxQVOPFHXp2zbpmeRZ5yhV8KvvTbg09es0cxQtDRfDrmHHqp8EOZdZNGihRZzqEKbNpU+R7USF6eFOwcNqtKhVIk77tC+dvPn63LHESN0yaO3VUJ5LF1qvSYuJ0enR1ZWw4bWXx2XSx8Lht1sQJHwzxQ85BCdznvJJTo9tVUrvebz2WfhHcd/brwRqF8/+O2zsoDXXiv+9113WadbDhzQ9cpENi64AOjRoziwczj0Guhzz5Weuk2xj0EdEVUNpzNwesXb+KywEHj+ed22VSsN1uymFPXvrw2tcnOLr04XFgJffolA1Tw2bACOOEKTeH376kmqb62QauGii4Cnn/aveZ+cXL6KoDk5wLp1wIsvAjt2aNbg+OM12/Dhh4Hr5pdDfHzZSYYBA7S0fxUmDKvE1q2le90B+rXdtk0bi5dXw4b2xWJSUio2xpIuvNA6kRQXp9Mny7J6tY7R96tnjF4fOPTQyo+xvFq10kbtu3fr74Bbbw2u4EyVSEvTxYblORAlFwb+/rv9dj/9VPFxUbUXH69Ttt99VwO8q6/WtXR33hnpkVGosfk4EVWdefOA446zfqxXL+C++7T6Rck5W/HxWrd95UpN0XitWaNRmV1/OrdbFxf51HQvKNCTyu3bSwcQ3j5gnat2yVhkZGcD48ZpVQ2HA7j8cs1k3nef/fGz0qqVzp3LyCh98Fq31pRnCC7zdu2qWShfiYl64hGRqXLQw/Xjj3oufvrp5W99OHWqnjwdPOj/WNu2+jWvXVsTMBdeGNw0SZfLOrDr3l0/jspasAA4//ziMaemaoGasoqcvPeeBkx5ecXxvsOh1xKSkjTm6Nix8uOrFvLzdb7svffaL3QC9MN++mlttAdo53S7sp2jR2smkIhqBLvm4wzqiKhqXXSRznkqWRvd7dYTlocftl6E43IBTz6pQYiXtxOz1Vmy9zl//63zroqsWAGceqp1WfW4OJ0aF7GeVeFWUKDRw4wZesyD+d3vdlsHgcZoM7mJEys9rHXrtO5NRkbxV6F5c+Cbb4AOHSq9+wp56ingmWd0yqAx+ueMGUC3bsHvY948nRVs1U7R4Sg+n09OBm6+WZPVgeTm6lfc6mNzucoXqwfi8ejPjYjOvi0rs7V/vy7l9A02ExN1+umwYbGXZQ2LTz/VCjZxcRoN5+Xpl01Ef+5atNB5uwsW6O+1tDStVuv7BXA69UtW1no9Iqo2GNQRUWTk5OhV5I8+0hOPhASt7DZzpqYB7H4HnXFG6SvTOTk6v8uuXFedOhq9FZ3c5OcDTZsG7pN17rnaXaFGWbxYOzO/9ZaeLNqJiws8zTIpKWTN4/LytKL71q1azb1Hj5DstkJ++gk45xz/dW8NGmj2znd6oR0R4LDDgPXrAydkAD0v37gxcGNxj0enWVpdA2nUSDPRwdi/X3+EmjULvohKIJ9+ClxzjfWP5SWXhCTur7727dMvfkGBfoiTJukHee65+iU8/XT9d36+/jy2bq1fFG8E37SpprPbtYvo2yCi8LIL6rimjoiqltMJfPCBrs1asULXyw0dqme7dgFdXBzQpo3/ft54w76aw7PPlrpaPWtW4JjD7dYZTTVOt27w3Hs/Zoxej7sv2oJnOozHZjS33jbQ1f+yIpVySEwEBg7U5ZSRDOgAYMwY66xXbq6W9w/kjz+AU07R6xa1a+t7CWYNV2IiUNY1S4dD6wC5XKXvd7uD6xCyf7+uTzzkEA02mzULTYEVn9nO/zHGf6zko04dTUvPnq0Vgc89Vy9k3Xabpm///luvLuTlaTS/apVeINu4UX+fbt3KgI6I/sOgjojCIy1NrzR7y+CdeKJ9SbzERD2x8XXZZdpQq18/PSFyOnWO3rhxxWtK9u4F3n8fez+eBbEJPBwOnd0UTP+umOTx6MmgRdBcUKCHb9Ag4OWPm2HYuotxOFbjS/QvvWFhoa6ps0rnGKM7iTK5ucC0acDkyXrOWxHp6fbXGgJVrfznH13/98MPeowPHtSaMiVnHdspLAyuG8WIEcDZZ+vXvlYtDaguvji4vmv9++uU1txcjQ/+/Vdn4y5fXvZzA+nY0XqKaWKirimkAB57TD/QiROLF2Gee64e0Jkz/b+IInphq2XL4EuSElGNEeREEiKiEJk2TdfKrVunJynedSReKSk6p+vww62ff/TRug8rX32la/gcDpxY0Bj5uSsAlM7sORy6yZgxmuWoVkS0I/Wzz+qJYf36OtW1RPT64Yfad8wboOQVxAFw4zJMwC40QBKK+j04HNrEKC1NK5l4P6O4OE33WDVHi6AFC4AzzyyeMZqfr+u5Si7LtOPxAN99B/z2mwY8Jde8eeXn63UIO6NG+WeGg0lmemfVde1a9rZOp/5obN2qSZzDDtOPZccO7UltZ/x4YO5c//tzc4GRI7XQSUU9/bT/jzCgWbpIFbmJCZs3a5Re8kuTmak/nN9+a//lycnRD84uRUpENRaDOqJYUlCg86jq1QvNgphw++YbrY9ecmFQXJxWi2jaFLjuOq2uUJFF/wcPltp3c/yFO/EyRuE2ZEJrvrvdWvxh3Ljw980Ki+ef10jGO39w+3bgpps0GqhdG9i+HRPeHoTMTP9OtAaCX3AcTsEPeofTCVx/PXDMMVr1Y8IEPZk8+WRN8URR9Yu8PJ1K69vY+4kntAjLscfaPzcrS2PXVausM07G6FsdNUrjWzuLF5ev/2FysgagXbvq0tLy/Dg3a6ZjPfNMHbcxWlFz8mT/aq7//KOzna0UFuq1lcr45hvr+CM7W2daB1onWKPNmmX9e86bpbNb0+pw6MFlUEdEPjj9kigWeDx6BpeQoBUb4uP1ZD2KzZ+vs4nOO08zBfn5AB580L/SQ2Ghvq+VK7V8d0WruH39td9zh+MhfGIGo/+hK9GnD/Dyy1qmvloGdB4PMHy4/4KwrCxtG3HBBcAttyBx3g82OzBIdMVr5Ot0Ag88APTsqRHDccdp2fT33tP2CFEU0AE65dHq/Dc7W3vFBTJ8uC71tAroAP1KjRunxUAC6do1uLYHxuiMu/nzgbVrdTZxeWfSZWdrsLpsmcbZOTn643P00Tqt9ptvijNn771nn/RJSNCAtiwiuuSreXP91dOhg/64AfbZbm8RR7KRlma94DI+XqeW230wLVvq3FsiIh8M6ohiwRln6PwwL48HePNN4KGHIjemAEaO1FYCY8dqdcmbbtIET/66jaW2K4QDk3AxztwzEf3OKsTUqcFV2reUn2959nqWTMeXp7+OH37QjEVSkp4I//STnliHsN5HZGVl2UcmBQW6WCwjA9d5xiAZ/tsl1ktBr9FXAC+9pJ2kH320igccOpmZ1mvXROyLpXqNHx+4oI4x2ri6LLfdFlzyxBidIduiBfDIIxofJybq1M4//tBsX1k/A1On6ph9t8vP18cGDdK+cYDO8rPLICYllV66um6d9rvLzS293ahRmkDfulWD59WrNVn7+efW6wyN0aAzNTXw+wiWiGZCZ82y72gSc84+2zqoKygAvv9ef/5q1Sq+UOVwaJT87ruxOUuDiKqeiMTErVu3bkJUI+XkiOh5jf8tKSnSo/Oze7eI0+k/1OS4LJmQdM1/d3gA6Y/PJRnpxdski1x9tc2OPR6R8eNFOnYUqVtX5OyzRZYvl9xckXnzRJbM3iseR5z1cbrjjv9289lnImlpektNFWncWGTRonAcmUo6cEDkjTdEbrpJZMwYkYyM0o97PCL169t/V0oc95swSlwmW1wuPQZpaSK//hqZtxUKH35o/XZdLpGPPw783NatAx8yt1vkrbeCG8eyZSK9egXeX1ycfoQ9e4okJpZ+zBi9NW4s8v779q/z3HMi8fFlftTy0UcikyaJpKRYj2PWLN3f5s0iXbvq8fL+XEyYoI8VFuqPm9X+GzfW51g9lpgo8uijwR23QNavF2nXTn83pKXp6736auX3GxV++knflO/BczhEmjQR+ftvkXvv1S/V1VeL/PFHpEdMRFEAwCKxiJUiHqwFe2NQRzXW338HPnOLMt6gyWqo52HKf//4ASeVCuhKnkQvX26x4+HD9cESZ8BfOC+SWqkFkpYmkpLikZbYKCvQyfrsPitL/v7b+iS0Th2R7OxwH6lyWL9epEEDPbP1Rr+NG4ts2VK8TX6+blPWmX7RbVWbc2TUKJGJE/3jw1gxb57IUUcFfquJiSL9+umPkZXHH7e+CFHy+7hnT9lj2bJF5NRTRRIS9Nakif0+GzYs/igDve7Eidav9f331oGa783p1LEfcUTp95icLHLxxbovj0ekQwcN8nx/ZH77TeS99zTQDPJr5fcefvyxIp9s8djatdMYx3e/c+ZUfL9RYdQokVq17KPz+HiRt98WWbVKJDfX//lbt4osWCBy8GDYh05EkcWgjihW5efbn1WlpER6dH5mzdIr/X4Xn1Eg1+Cd/+54EE8LUGh5Ev7SSz47zc72O4v9C4eKGxk+zy+UBtghuUjwH8AVV8hjj/lnRwAd76efRuRwBee00/zPbOPiRM4/v3ibKVOs35zd2f6wYZF7PyGwenXZgdF/3z2HJjH37vXfT1aWZs1SUop/zIzRfdeqJTJzZuBx7Nghcv/9wR96QKRZs+CCskMPtX5Nj0fk+OPts2QlbxdeqEneYcM0eOvaVTOPBQW6r0WLrI+jMSKtWgV/jK1uxohcfnn5PtfCQpFvvhF55hm9Wb1HY0Quuqh8+w2r/HyRr77SzPrChf6Pf/RR6QtUgb64KSn6IVx6qf5yPXBA5Jxz9GfYm7p84gn9UhBRjWAX1LH6JVG0i48HLrlEexn5euqp8I/HgogWb3A6gZNO0nLmvmuZnMjBDXjrv3/Xw14kIRe5KN2hODFR6wSUsnGj3zqSd3Et8uFb8cSBHCRhBk5HP3xd+qGPPsKuy99BXp5/lZTCQm1vF5U8Hl1j47v4r7BQFzXt3q2tC6ZPD1x+MT5e1+skJ2uxhTvvrMpR66Kvjz7Sjt1t22rVnBCWQnzhhcBr4UryeHTJ4XvvAffcU/oxl0uLe86erevJDjlED6fLpevcAq2T274dOOoo/e5YrelzOPRrW7KIS3KyNhEfMaLscW/ZYn2/MVog8YUXtBDM5s32+/j8c+0OMmyY9TLJnTutaxOJ6H4rs+ZUxLqRu530dK0PsnatPs/32JXc786dFR9Xldq8WXs57NqlX4q4OOD447VNgbeSTskKtYF4PMXrZCdO1DKp8fH6c56XV/wDMGKENiG/5JKqeU9EFBusIr1ovDFTRzXeLbfovC7v/KMXXoj0iERE1+w0baqJo1q19Or677/rFLPUpBxJw35xIktewW2lrkL/i0MsMm2aNTtwwOdF9u/3myN3Nd6xvLidjIPyPq70fyAuTr54f7dlhsTpFFm3LvzHTrZt03mBga6yb93qn6UreevZU7d78MHi74fvrXdvkYcf1rTJ2LG6TrMq7d0r0rZtcZrH6dSMw2+/hewlevYsf+Zo8ODQvPaBA/rj17x52VMTGzXSH9datXQJ7G236cd98smBp30CIocfHtx4nngi8H6Sk+0/8l27rMeRkBD4axfMLTm5fBnwe+7RY1TWfl0ukVdeCX6/YdW1q/Wg7767eJvatSt3YK1uRx0VsbdMROEFTr+Mfh6PTj0hihXTpvnPInLHZcuTDV6V/Btuke/fWiufJ14oe2F9EjMdZ0ot7JM07Jc0HJB6aXny8882L3b11aXmYn2ECyUZB/0DNGTLXzjU8vUKdu2VPn1Kjzk5WeTWW8N62LQyxbHH6hmsyyXSooXIJ5+IvPOOyOTJIunput2iRRrlBjq7drtF/vxTo1KruWqpqeFfMHjnndbzEQ87LGQvceut9jGsXSAwfHjlX3fPHpGWLYOb+piSohc9li8XmT5dY3ivrCw9TLVqWQdQbrfIl18GN6bCQpE+fQK/961b7Z//xBOlp1k6nTpdNZgZgt7bZZfp19m7Ni8lRWcJeqd5BuOQQ4J7rUMPjdJ1oLt320f5LlfxdqecEvyBDfbWuHHk3jcRhRWDuiiWna1Xb91u/f+gRw/rafhE0aZLF+vzi1QckPx4p16RHjtWz1zT0ixTArlIkB9wkvyM4yT/wovtXyw3V8sGFu0jD/HSE7+WyvYlI11ujR9tPSinU2TVKsnLE3n3Xc2UnH22yOefh3k5SmGhllz0rUzhPfFLTNQz/C5dNNgr62Su5MKvTz8VSU2V7Slt5O6EV+Xw+LVyUrf0oIODSsvO1rKJVosqAT3r//ffkLzUhg3+L+N0igwYINK9e+mY0hj9Ku7aVfnX/b//C279XHy8JiuDTYp+/LFI+/Z6iDp10gsmJRUUiHzxhSbsn3nGP0jLzdWiIpY/j6nWtTZK+vJLjTW6dNH1dxs2BL+eLiFB5LXXdJ3jAw+I3HCDBrHlvUjZqFHZr+V0Vq74SpX699/Ag/dauLDsNG15bg6HrrkjohqBQV0UGzDA//d7SooWvCOKZrVq2Zy7I1t2oZ6ebFx2mZ5Rfv+9yA8/iPz1l/1Jv9stsnSp/wt5PCKvv66X6EtUi8tGkozCTdIbc6UvvpMpGCge47C+Wu52i2RmhvsQ+Zs92/79V+TmdJaKVnZuyZFGdXIlMaG4CE1yssj//lfF72vzZi35GKgCSGKiZjNCZPlyDUSSknS675NPao2KAwdErriiOD4+8UQtIlhehYUanDzyiMjo0SL79umUyGACuhtvDM1b/egjkSOP1MDJex0gKUk/U98iLnPnWmTO3doCoSJ+/FGkXr3iFiBut3V2NDVVZOrUyr/XO+8se/ql2y1y1VVa0fPYY0XGjYuiGiEej32mLjGx9LaLF2t7lor8zHt7X3gj6tq1ecJAVIMwqItSGzbYr2cI+5QwonLq3dv6nCMO+XIzXpNNaK4n+r5uu836iUlJIiNHlto0PV3k54tfl9XOo4I/4fFNMSQnizz1VHgOSlnGjg2u9GEwt+RkLb1YwoMPWp8Yu1xVXP38rLOss49FN48jTks2hlFlprRnZWnQ4P2ovEFVoOxVUpK+xVDFrSNGBH69evX8pzfOnq3LuhIStMrm6NGVC3ry80V+/llbCPzzj/X1iNq19Uf6//5PZOXKir/WgQMinTsXH/OSU1JLVib1/RG47rqKv2bIDRxo/Ttp6FDr7XfuDDyPOC6u+EKW06kfwHvv6dXgzp31RGHz5rC+RSKKLAZ1UWrGDPtsR5jPf4jK7aefrNYWefQkGLlSC/tkTYcB/k8cMcL6akZKijYYL/LyyyIul0dqYb+4kSHd8ZtsR8PAgU6nTlqp5bTTNL3Qrp2eBEXL5fxVq4JbkBXoJK92bZ1jOGmS3/vq1s36aWlpmsmpEgUFtgHdVAyQQ/GXGHikUYMCGTUqej6KQJ59NviPKS5Ov3Z//VX2fnNyRDZtKntaZlZW2dMfU1N12WU4zZ+vs4ddLg1i69TRvxujx8Hl8rsuUy75+TrN9IkndInpmDEiZ5wRuNl6xAodWUlP12bh3oaFiYk61zsry/45LVva/9Cmp2u/uquu0i/l9u1heytEFJ0Y1EWpzZvtM3V33hnp0RGV7YcfNJAwRcFcyZsDBTKwh8VV5G3brKsw1Kr1XwWEGTP8N4lHnhyDX61PgIyJna7EF18cfBUKY/RMOSVF/+zfP+ACqQEDrHfjcgUXdASydq3IeefpuWbz5hqbFxSInolbBHVf4yy/Cqdut0UfwigUzDRLbwuxTp00ixWIx1NckMTt1j8DtRdbubLsWbrJyToFNdw8Hp3t98kn1oGn01n28SiPCy4o+3P44IPQvV5ILF0q8uGHwX1AY8ZYz5t9/PEqHyYRxR4GdVFs8GD/K8KpqXo1lygW7N4tkpjoH9QBInXq2Jy1zpwpUreuftlTUnSaZomS92eeaROcILO4uqV3bUlKiv4g/fFHmN5xJRUUiIwapdFAq1ZaFdJu6mJyss5/Gz9eZMWKMnf988/+54cJCSLHHVe5IW/dqgnCklPi3G6R66/I1qjeYvxdsMTmOxGZSr+ZmXqOHcz0yLKWO6Wk6HTDRYuCyzy++KL1efvLL1tvv2dP2bU0WrWKbNbz9tutl5AlJ2sxolCYMyfgrN7//r/89lvdfssWnZF88skid90lsnFjaMZRYVOn6mwBh0OvhFgdGI9HS7OmphZH/fffz3LYRGSJQV0Uy8vTFlJ16xbP1IjE1VeiisrOti9w0KaN9XMWLhTpe2qh1E3LkyPbZcqUT0qfwNi1e0rDfpmPY/RMLylJ52UlJ2v66Ndfw/Buq4DHY5+WiY8vd1+599/Xw5GaqoFBnz6Vr/x4773WgXuSI1e2xTezHHuKRcsJb5C5f3/lxlMeHo9WjHS79ZgkJYlcckngTg8vvhh4+mVqqtb+CVaDBtb7adjQ/jkXX2wd2Lnd+v/F8OH6f8e4cYFn9/navl3Xc1c2ILzvPuuAy2cWdaX06BE4oDNGrwcVFOg1nbS04uqkCQk6liVLQjOWcps2zf9L5HbrQkcrubkahZbnwySiGodBHRFVqSuv9D8Bdbu1aKWvRYussxZvvVW8zSOPWAeKyUiXrHrNrB9s3Dh2r27bLa6Nj69Q1c6cHJ0BFqg/WXn0Pirdcni1sE9m42TLsXfFIsvn1K0b3o9pwgT/75vLJXLttfbPyc0V6dvXOrAzRpMu5enBZlcU0eGwf05Wlv5cedsZ1q6t/37nHe124Q1e4uL0mJY1u2PrVs3YlmyPWJn2AMuWWR8ft1srhYZCoGxlQoJmVL3r6U491fo4H3tsaMZSLn/9pSlpq4GnpGgqloioAuyCOgeIiELgjTeA008HnE6gVi3984YbgJtu8t/2oYeArKzS92VlAQ8+CBQW6r/vugto0ABISirexu0WvPiSA66OrYHcXCzG0RiMD9ENi3AnXsLWA6nAkiVV9yar0vnnAwkJpe8zBjj2WMDtLvfukpKAo44CmjYNwdjy89Fx9VTEId/voVwkoRU2Wj7tOcejcJnsUve53cDjjwOOcvzvs3gxcM01wFln6ffM97tTlmef9X9OdjYwcaL+aSUxEZgxA/juO+DSSwGXC0hNBZKTgbZtgdmzgbi44MfQoUP57gf0NT/4ANi9G1i7Vv/84ANg5kxg82YgL0+3KywE9u7Vnz87Hg/Qpw8wfz6Qm6vve/Nm4JxzgE2bgn8fJR15JPD00/qznpwMpKTo5/vhh0Dt2hXbp69DDrG+3+kEVq4E/vhDPw8A+PlnjZp8LVig7z9sVq4EunYF9u2zfjwjA2jeXL9cREShYhXpReONmTqi2LBli8gvvwS+EF2/vvUFbKdTa6h47dmjtQJ69NACIP9lFY4/XqbhHHEjQwwK9Ko9cqQO9sr6qUur8N1VoZ07taygt567260169esifTIRL79Vv5M7u5X9CQJWXJm/Az/DzIuTuc3Hjwo06Zp0ZG4OC2x//bb5Zv298EHeii8a/ncbpEOHbQoYLDsvm8OR/AFPXJyRObN02WN5Z22uH+/ru/yrVzvdmtBoPIKVAHfbprtjz9az/BNTBR56KHyj6GkrVv1cx03LnQZOq+337bO6g8b5r+tXWLM5Qrz2sPTT7f/gHwzdtHQO5OIYgqYqSOicGjWDOjdG6hb136bFi2s73c4gDp1iv9dty7wxBPAb78Bn38OnHSS3i9XXoUbMAZZSIZA0yX5SMIBpOGRj48IyfsIuwYNgD//BEaPBu68E3jhBeDvv4H27SM9MuDgQXRwrMF0nI32WIN45CMJORiCj/DpcSM1RZOYqNu6XED9+sDzzwOpqejXD1i1CigoALZsAa67ThOQwcjOBm69VbNs3kxLVhawcSPw1lvBD793b+v7PR7gm2+C20dSEtCrF9C5c/DjBzQz1rw5MGaMvp7Dofs66STg22+BU08Nfl8lxx3o9az884/1/Xl5wPr15R9DSU2b6ud6+eWhy9B5XXut/g5ITdUsoNsN3HEH8PDD/tsOHapfv5KcTs3yluczq7RffgluO4dDU75ERCHAoI6Iwu7xx/1nFLpNFm7s8BOSDuws8/nbTr8Sex31/O73IA6zv4/hX2tOJ3DZZcDLL+u81bS0SI9InXQSkJODkzAHa3A4dqM+DiINH+BqJCNT58DdfTdw3nnAsGEaxYVg3ueSJdbTNLOzgU8/DX4/d9xh/9jLL5d/XMEqLNRDkp4OZGbqvz0eID4e6NEDuP56ncJZt65OYwx2imCrVtb3x8VpPG2lRw8g33/2LJKTdVpmtDIGuO8+nXq6Zg2wZ49Op7X6XgwbplN0vVPAXS7glFOAESPCPOhgI1sRvdpBRBQCMXz2QxQjcnL0pHf37kiPJGqcey7w2mtAfXcWnMiGG5m4Ud7A/5afpQvByjhWaXXjIfGJlo/V84/1qLJmzSpe7AigFg4i0bu+bv58zdQ995xmGVu1ApYuLbV9RaWlWQciQOBMsK+mTf0zOF6rVgEbNpR/bMFYssR6/V9mJvDSSxqkALr06rnndE1pMEaPts48NWkC9Oxp/Zx27YBBg0pfTElM1OO4bx8wfLgmiqNVYqLOAnA6A28zZYq+j0mTgOXLga+/tv/sq8zddwe3DragoGKpWiIiCwzqiKrSa6/ptLpevfTM8vzz9YyOcM0FB7Hd0xAb0Qp7URcv4j7E52frGeYrrwR8bkoKcN5AU6qICqBZh3vvrcJB10S//KIpJbs0UlKSVtoYOlTn1V59NTBgANCyZXHUAn36d98BTz4JvP02cPAg9Gdh9mzbShZ79+o1EV/JycBttwX/Ftq108yNFY8HeOqp4PcVrPx8DSjsirr4vt2sLP11EUwRmNNOA15/XQ+906m3Qw8Fvv8+8DTDsWN1VmzHjvrxnHwysGuXfiaPPgp07249rTHWtG4NnH12cQGVsLvzTp3z6U0ZJiXpz0Zysn5AiYkaab7zTvRk44ko5hmxKhUVhbp37y6LFi2K9DCIgjdtGjBkiP9ZWsuWegm5pv9n/vPPQP/+wIED/o917KjZzQAyMoALLwR+/FHPmXJzgdtv14xDWNfPVHcDBwJffGFdVhDQg9+okZZSLMkYPbv+6y9k5xiceiqwYoV+bsnJQLwnDz/KSeiS+KdGOHXq6AK3Tp2wa5eupZo2zfolb7gBePPN4n9v3w78+y9w2GG6byvvvaf7tNK6tS5fDJWCAp32t2RJ+a7hpKRokrNNm+C2z8jQeLh2beDoo8v3vd+5U38V+QbNbjcwZw7QrVvw+yIbe/Zo2dJWrbSM57x5wFdf6e/+iy+2n0dLRBSAMWaxiHT3vT8+EoMhqhGGD7e+7L5pk065+e234rOwjAwNclwu4PjjddFNdXfIIcU12X2tWaNnnQ0b2j49JUVjgM2b9dapU+kiKxQiGzcGDuhq1fIP6AB9zs6dwNKlGPltVyxdWtw+QAOdeAzGB1idczgMoD8Dp54Kz+at6NMnvmSSrxRjgG3bNMnRurVmt777TpMf+fmaabLKNg0YoMsUrb5yzZqVdRDKZ8qU8gd0gB6yJk2C3z4lpeKz9776yrolQ06OtiRgUBcC9erpLA2v447TGxFRFeD0S6Kq8u+/9o8tWaJTdA4eBMaN00zHkCG62KxJE6AmZKXbtdOzcitxccD77we1mxYtNA5mQFdFTj21uLKlr4su0sDNjsMBpKdj7FirfnAObEFzbESr4ruysjDntWXYvNl+SZ4IMH26Fj854wzgyy81EDl4UF/j2Wc1KPFVr54mhn2n7Lrdwa9lC9YXX5Q/oHO7gXvuCd/6r0BZPWa6iYhiD4M6oqrirb9vxePR+WMdO+pcsqwsPStNT9dFLqefrvMJq7vrrrMuY5eXB6xbF/7xkL977tHpYiWzx8nJWmf+yy8DP9fjAY45xjZIEAAOlF5ctn6dp8wqkAUF+iNTWOifRMzK0iS5lQ8+APr106VOqal6e+EFrZgYSvXrl68xeYMGGow+8URoxxFIv37WgXNSkl5foij25Ze6RtsYrXTzyiv22XQiqjEY1BFVlccf908LlJSXp4uBrIK3ggKdU1bd9ehhXYDD5eI0pWjRuDHw+++6IK1VK+CYYzQ6OvrowDX44+P1woXTiWuuscpAedAaG9ESJaZu5uXhqPNaVzpTZJc8TEnRVghbt+patN27dUpmSQcOAPffrxngQw/VYKu811euu84+uekrKQlYvVozj1WVIfN4gLlzi987oIHkW2/p5+J0AgkJ+vd77tGPtjI2b9aiLF9+WTOuTYXVuHE6l9g7E2TfPq22OWxYZMdFRBHHoI6oqrRureXeAwV2VqkGQAO+/furbGhR47PPrO/Pz2e6IJo0a6YB2oYNGg1dcIGeTNplB+LjtYLNpZcC0AI2xxxTVCAlHkhJEdSJS8fHziuLn5OcDDzwALqfWR89epQuXW+M/tsqqevL4Si771q9ekCHDv6BV16eLoF69VVtlL5hg/aP69evfImQI4/U6pRutyY509I0K+gbtCUl6fm5XXuG9HRtvl6nju7jssuAHTuCHwegAVb79loN8tprddbznXfq+7niCq3j8eSTWlGzbVtg4UKd3mqnsFDfW+fOuv0DDxT/qhLR+KJ9e+CWW3S8TZroNQEKkZtv9r/P49GrD3b9P4ioZhCRmLh169ZNiGLS+vUiJ58souc8wd+mTIn0yKteSor1e3c4RLZsiezY1q0TOeEEEbdbpFEjkZdeiux4os2mTSJOp/9nl5goMm6c3+Yej8gPP4g895zI2LEiGXtyRN56S+SUU0QGDhSZMeO/bbOyRP7v/0QaNBCpVUvk8stF/v1XpG9f/WrY/cjEx+v2f/1Vsbc0ebL1VzI5WWT+/PLta9UqkaeeErnxRpGpU0UKCkTee0+kTh3dX1KSyCWXiGRmWj/f4xHp3l23K/lj0ayZSHZ28OPo2lUkLs7//UyerI9nZop06CDicpV+/IknivdRWCgyapRI27b68ZbcX1KSSPv2+pldeqn153LIIboPqqTt2+2//MaIbNsW6RESURgAWCQWsRJbGhCFS48eesm65EIWh8N+CtvAgcDUqcHtOztb911QoCmBqVN1Hln//kDfvtFb+cDhsE+B/PNP+UoBhtK6dcDhh/t/NkOGAJMnR2ZM0eiBB4BRo4qrgiQn69y977+vkgqu69drc+3sbF0753Tqyxx9tC5FPeEELXpS0Urxt9+u1TR9OZ269u6WW4Lbz0MPASNH6o96XJz+eeSR+lhKiu6vf//iVmZWfvxRM4RWBVdGjAiuH+OGDVoV1r9IDdC7t7YgHD1a9+VbqNfp1CxfgwaaHBo71r6HXnKyNjafMMH611lqKvDtt/qaVAnbtulaOqvfmcboXNeEhPCPi4jCii0NiCJtyhSd+1QyqAu0JilQ9UyvggI9E33rrdL78gaL772n86qmTAlu7lq4xcfbTxlq1Ci8YynpmmusP5sPP9Sz/vr1wz+mMPJe/i/5lfF4NM6uVatEi8Xhw3Wu45gx2pLg4ot1ymUVteRo0wb46y8NmEaO1CAjIUGLxY4cqT3Sy+Off3SqYWKiFp499FBdV+YbBCUkAM2bB7fPBQu0boXvPnyvSf78swZUv/6qgZ6v5cutgzFA32swQV16un3Blm3btCXI1KnWwVpioo7tmGP010igtXGZmforxu7XmTH274XKoXFjbS64caP/YyedxICOqIaLwrM8ompq5crgqyc4nboIpiwPPeQf0AHF/87MBGbN0hrr0ejEE63v79mzfOUDQ23xYvvHPv88bMMIt4MHgauv1sAmIUEbaK9dq0sfmzTR5t4NG2rT9/T0oiedeaZGBjNm6JOD/Y5XUK1awKRJOtb8fB1HVpZm0ebPD34/L72ka8LuvFPXrTVtqmvbfM+LHQ4NYoOtkDlpkn9DbyuZmZp5fP1168fbtbMPkv79t3S/vawsTcz76tjR+uMwRgPaiy/WpKpVIt/j0WsXK1bYZxO9kpICB32FhczShcy0aXoVwPuhGaNrXqdNi+y4iCjiGNQRhcuqVcGVgktK0rOp224LvF1+vk59K6v+e0aGdeOuaLBpk/X9TZuGdxy+kpPtH7PorZedrZmXZctit7K4iHbSmDRJv6Yej04B7N5dk287duj7zM3V88eLLorMOBct0gqOvsc5P1+rTgZj5UrgkUc0+MrK0h+R7Gzgxhv1WkrJQMjj0X/PmRPcvj2e4L8D2dn2P5qnnx44uf799/qZ9O8P1K6t0yS7di1dlCQ+XguVut3FyVNjdHx5eRoIWo3XGA3ee/XSqaxWDdtL8k6BtWIM8Pbb4eu/V+117qwR+Vtv6Zf4yy81c2eV7iWiGoVBHVG4dOxY9vSYlBTgvvuApUvL7qZ98KBOvyyLMYErcEbK3r26aMfKTz+Fdyy+7rvP+v7kZG3GXcLYsXpC3a+fdmE4/HCdIljK/v06h23kSA3uo9Bvv2mwU/IEXgTIzBS/qXO5uRrw2X18VWnPHvsZu6tWBdf0e9Ik60AlJwf45BP/xzZs0OmZS5eWve8hQ8oXwNidi8fFAVddZR3YGaMFSFu21LVq+fl6W7pUZ+GVrJDZv78mnm++WWfKBjNDLy4OePFFfZ127YBjj7X+FeJ0auuHb77R60u+79vhAN54QzOCZVmzRrvA3HcfMG9e7F4cCYu0NJ1r/NRT+osnkrMaiChqMKgjCpfTTw8cqDkc2jTrqae05npZ6tQpO/AD9DL9NdcEP85wCTSnK9JXne+/XwvVlOR269lmCUt+y8dNN3qQmakxdmam1lg57bQSCdRZs3R61O23a2GRbt20KVlFz1oPHNCa+5deqmXM7ZqyldOaNdb3ezzWRXYSE4t7ntn6/Xddd/f661rJJAR69rRumg1oxqjMMaE4E+lLxH7f2dl6uMty3HHA0KEa4JRVnyg5OXDxlZEjgS5ddLuS+/J49LuWm+t/XSc/H3jnndL3HX64rvN78smyp1ICus+rrioOkD//XIPapCS9tWqlGcY//9Qk0Qkn6I+Hr4SE4JbGjh6tWcZnn9Vg8vTTgRtu0M9j924t6PLPP2Xvh4ioRrMqiRmNN7Y0oGph6lSRhATrktQJCeUv4z9hgtYYt9qf06m3hx6qmvcSCued5z9+t1vkf/+L9MjUtm0ib7wh8s03WmO+pNdfl2sTPhAH8v0OfUqKyNy5orXn09L8PxuXS+S778o/ni1bRBo21GPk/YzT0kSWL6/0W124UEvZ+7UJQJ7le3Q6Rfbts9mZxyNy3XX6Po0pLrk+dKjW9heRNWtETjtN2xAkJ4vccot9eX9fhx1m/5VPTy/7+b/8Yv1ey7p16hTc+EREfv9dWzJ4375v1wenU9+z79fKl8cj8v339j/mVrfLLiu9jx07RF54QeTmm0u3SAh0S0kRGT++9H4yMnRfVmM+5xzr99q0aeD3uGOHdWcMt1vk/PP1sVq19M+BA7V1AhFRTQablgYRD9aCvTGoo2qhoECbNvmewTgcIp9+WrF9Tp8u0rGjnq2lpYkMGSIyerT2ANuwIaTDD7k9e7QZV3Kyjt3p1PHn50d6ZIF98omI2y3nYJrlCXFamsgXX4h+NlZnrIBIv37lf93Bg/2bjgEiTZqItG4tUreuHr8KfO6eQo8c3+ZfSUJ28dcS+VIHu6UW9kpcicAuOVnk4YcD7Ozrr4sDT9/b4MGyc6f2aysZBCQlaTvHYPz6q39w4nKJ3HVXkO/Vo/3j3G4dQ6Ded95bXJzIVVcFt38R+8AxPl4/+vJ+RHZfI99bcrLI668XP2/ePA3QvM8PNqhLShIZOTL48dWpY7+fXbvsn/fBB/btKuPjS//b6RS5/vryHbeyrFmjx2v8eJGDB0O7byKiqsCgjiharFwp0ry5nsmkpemZ5QcfRHpUkbVkiTZbr2jX6HA74ggRQN7E9eJGumXGaOdOEfnsM/uz5ubNy/+6qalln407HBrcbd9evn3fcYdkuOrLLXhVUnFAEpEj52Ca/I1W8jdayeUYK41de+WII7S3eMAM0+DBtuNbm9BROrTJsXzY7RZZujS44c6YoU2zAZHatUWefPK/JGBQPB4NvO65xz4g8c1crVkT/P6vucZ+X+efH/x+RPR9tWhh/3GXDIKaNi0OTjwe++eVdXO5RO6+W+T22/V6U15e4DG2b2+9H6dTJCfH/nkTJ9oHdXb7K2sswfB4RO64QzOgDoceO7db5KefKr9vIqKqxKCOKJoUFoosWCAya5bOaaLYUreuCCBZcEonLBcXMoszJe5CefLJou2WL7c/O61Xr/yvW79+cGe+SUkijzwS/H537iw7heN0Sv71N8mLT2dJu3YizZqJ3HmnJlv9XHSR5T7+QWOpjX0CeCxfIjVVZNKk8h2SwsLybW/F5QocRJxySvDBpohOvbSbLul2i7z2mv9zPB6R3butp6C+9pr1GOPjNehq0kS/kldfrTOGvdassU+YlhU4xccXZ/dSUkS6dAn8q+q99/xfy+XSGbeB7N9fvjHGx2vQmpcnsnVr4IAxkOnTrTO0TqdIbm7F9klEFA52QR0LpRCFk4jWvf/hB61ecOqpgcvnU+Rs26YdoK3aUHTrBgBwIQcLcCyewUPohV9wTsIMTPkUeOyxou1atPBrxC0ARuFmtE5f/l//s5UrgxzTtdcG19g7NxeYOzfInQL444+yK2jk5GDwe6fj0Uc8WLdOC5K88QbQo4dF8+rLL7cc5yu4A1lwAbCuIFJYCHToEPywgcBl/4PVubP1/U2a6HubPRs46qjg9pWXBwwaZN8GIDkZuPLK0vf9+KNWmWzSRGsfXXSRFt7xeu016+bdDgfwxBNaRGTPHi2wesghxY8nJOivnGAZowVLCgu1WIq3315GBrB6tfb2s3PVVVpfyOXS4oxOJ3D++VrTJ5BatbToisulx6as6pytWun7bNBAm9EnJwPt2wPjx9tXRbXyzDPWxXJycrRLABFRzLGK9KLxxkwdxbzNm3Xtm3f9mMsl8uKLkR4V+dq7Vyt4OJ2aOkpNFXnnHU2jXH21/tvt1pRByUVhVtNoCwv95r/di+fFjYxS2YGUFJF164IYW3Z2cIui4uN10Viw1q8vc9HWSnQslZH8LzOZLPLuuz7783hELrjAbx/HY47tSxgjEo5f8zt3inz0kWZqvBmZH37wzxa53eXPGoqIPPig9bJHQGshvflm6e1Xr/Z/7cREkWOOKV5a2qSJfUZt61b7sWzebP2xejNxvsndYcMCfw0OO6zs95+RIbJsmf64lMeePSLvvy9y5pn2r5+QIHL//daZvYQEkZNOCn45brNm9q/zwAPlGzsRUTiBmTqiCBLROvd//on/6t9nZ2vz2NmzIz06KmnQIO2Tl5MDpKfr7bbbNJUybpz+25uacru1ZnvPntrgzDcF8803mkIpsh+1MAq3Iguls7PZ2cBzzwUxNqczuHREUhJw551B7LDIoYdqXfoA/QwXogcc8K/3n5lp0VbQGD0eb72lqaeEBCAxER2b7Ed8vHXqSET7zC1aFPywy+uFF4DmzbVJ+eDBOrTTTtNM2YQJ2o6gdm3NVn30UXD91XyNGWPfFsHhAM47r/R9I0f6J4Pz8rRvYL16mpXq3986QXvIIZrd831uZqYez759rTOGxx4LzJypH3mdOto4/NNPi7/2doLpcZecDBx5ZHBdWUqqWxc44gi/riH/iYvTjOXUqRaZYeiPxcKFwGefBfd6gTLC3bsHtw8ioqhiFelF442ZOoppv/1mXe8bqFgVRKoamzYFX2YQ0Kzd55/b7++KK0pt/xu6Sxr2W+4q6HL5bdsGTmW0baupJwurVok8+6zI8OEWmcGDB0V69LDd9yycIik44PdQUpIUryG04vFoOmnPnqDWeJ14YpDHoZzmzSv7tXv31mNUGYG+Ps895799nz6Bx+R2i0yeLNK4cfG6uoQEvb/kx3zggMgll2iWLz5epE0b+7WC55xjPfaipaKWN5fLei1gqOTm2r9+YqJ+NQsLy/4MBw8O7vV++806o5qcXPF1ekRE4QBm6ogi6KOP9JzBysaNYR0KBbBjh3bVDlZmJrBiRdCbt8Qm5MI/G2aMLrEMyvPPY6uzLd7HVfgYFyITbk3jvPqqrgNcuxbo08fvac8+qxmZxx4DHn1UsymvvFJig9RUTVPZOBk/oCF2IQ6lM4XxpgDXbX8aGDUK2LvX/4nGAE2bAnXron174LvvAr/XqsrUvf229bq0kubN06Trli0Vf50+faybjnfsqL3nfR13XMAEKbKytDn3n38CTz0F9OsH3HqrLvf0fsy7dun+J0/WzFxBAbB+vf37/eYbzWr5at7cfhynngrceKP948HIy9PX/vBD/aqWNGuWfyN1ryOO0GXIDkfgtY0Oh2Yeg9GjhzY6L0oiIylJ1wLOmhX48yAiilpWkV403pipo5h2+eX2l5YHDoz06MgrI6N8pfhSU0U+/NB6X/n5Wl/e5zlDMNFvbZo7LkcWfbAiqCE+84yIM6FAkk2mpOKApDrS5cdnfwn4nD//tM7aOJ0+/dIGDgz4fregqZzg+FmSTK44kzzSJnGzzHOdUpxSSksTWbSozPcQKOPSokVQh6HcBg0K7iNNTAy+352V1au1WbZ36WNioq6ZXLzYevvt2zVDZZfIB0RatbJ/vd27tcl5sF9Z7+3ss/339cgj1tumpZXdJL0sS5Zo8da0NP2xcTp1DZ/X5Mn2HTsuuaR4u7lz7b87Lpe+Tnns2iXy8cfaWpFVL4koFoCZOqIwKizUS+zr1wM33KDr5qwu3xsDXHNN+MdH1pKTgaef1rVywahVy3+RlNfXX5cuYVjkA1yNqzovhhPZiEc+DsV6TC0cgG439wQ+/jjgy82fr1X7cvLjkClupCMN6Z4UnDu8d8C1UFOn2i/F++KLEv+48UbraqxJScBZZ6HZOV0w592/sHUr8NctL2OdaY9e2d/rNllZ+n6HDLHPShdxOICbb/Y/zG63VlCsChdcEFyh2bw8Pc4Vddhhujbwnnt0vd7tt2tx0aOPtt6+USNg8WLgwgutH4+LA44/3v71Xn8d2Lev/OP84w//++yypPn5min0yskBJk0Chg3TNWx2GTavwkKt8rp7t35F0tN1H8OH63pGQLOOVt/R5GRg4MDifx93HPD995ppM0a/S263Ljd98UVdD1ke9evrsT/77PIl6YmIok0QtbGJKGh5eXpW+vbbWv3A49EzD6va2YAWqDjnnPCOkQK76y5I+8Mw94GvMG9lGg7BNgzCFKQgEwCwBF3xAa5EZv3WGPRMb5yZkGR9dWzNGsv5b0nIwxsJd+CVuFXILkxAKtK1wH8WNNI5/3zbtgXvv28/pW7GDODcc60fczisrykAPveffroWWHnxRR2Dw6FnurNmlZr3Vh8Apr0J5FpEkps26a1VK+sXLPLcc3pyP3asToErKADuuksPQVW44AL9sVywQGfN2omL0+l+ldG4sQbfwWrVqnhK4s8/l34sIQF4/HH75377rX1QlZCgAZXvrx9jrNs4WM2e9e7nwAH9++bNQK9eGpxlZAApKVqsZd48++Ioc+daFzfJytJaOn36aNGXRx/V45adrdcFkpOBY47xv27Ss6cWkiko0OIumZnAiScGnD1MRFT9WaXvovHG6ZcUE668MnAnY99b/frafZeiRl6eyOmniyQ78yUeeZKCg1Ibe+V3HCUv4Q5xI0PikP9fUYXzz7dpgD1tmvV8spQU+/lycXFaXGXtWsuxXXaZ9dNSU7VMv501a+ynX27ebPGErVtFJkzQOWl5edY7Pfxw++/1vfeWeZy99u8XWbkycGPrUMnPF/nkE+2N3rKl9ZTH5GSdQhmIx1P56Yi+fvnFelphYmLphuK+LrrIfupm7doit9xi3a7ht9/89zV8uPX3JDVVu2mIaLcP3wIjiYki115rP8bp0+1/LZ56ault58zR7/m554pMnGj/9SMiqqlgM/0y4sFasDcGdRT1du0qX+VE7yKQl16K9MiphFdftTq5LpQW+FucyLIMAqZPt9hRQYE29kpIKN44Pl4XjR19tP13Ij5eBzBzpt8uv/xSX88qONuzJ/D7euEF3S4pSf90OkVGj7beduZMrcbpcGj8OWKERRAzYoRuYPUeUlJiYoHSwoUiJ5+sQUlcnL7nn3+23/7PP7VapcOhP7rXXy+Snh6asdx5p32Q+c479s+bP986GKxTR+Tvv/WCw/Dhev3I4RA56ijb4qhy8KB+Zb37czj072PH6uN5ef797Uquu7Ozd6/9171v34oeMSKimskuqOOaOqJQ2by5/IsysrN1PhhFjXfftZoq5sB2NLbt0zZlisWO4uKAX37RNWYuly76OessbQh23332C7wKCnQAV1/ttzbtnHOAM84ofmp8vO565Ejt8xXIPffoOqpnn9Wpj2vWWFcznDcPGDBAt/V4tLLi449bTAG8/XYgLg470QAP4Wkcg/m4EB9jPnrqE3fsCDygKNC9u1bjzMzUqaArV9qvX9u5E+jdW6f7eTz6oztunK7FCoXERJ3t6suYwP3hevbU3ni1amkBU6dT+8+tWQO0bq37/L//08+xsBBYutSyOCoAff7ixcD//qczca+8EpgzB7jiirLHbze9FwC2b7f/1fj332Xvu7IKC4F33tFj1bmzrnW84gotShxM20ciophgFelF442ZOop6Bw6UP1MHiDz1VKRHTiUceaT1x5SEbElGut/9DofI7beXsdO1a7WEoTF6q1tXp1k6nfZz5xISRDZu9NtVYaHIt9+K3HCDyH336dRFSx6PpkjK2XTr1FOth5OcXDwFz+vfnudJQ2yXJGQLIGJQKG5kyKTEK6K+2desWTqD1BidXvjggzo9086wYdY/3m63yO+/V348S5daT1F0ufRjLEtursiyZSJbtlR+LIGceab19Mvrr7d/zrZtxdVAfW/HHlu14xXRoq5W2cyUFO1/5/u9JiKKZmCmjqiKpaVpA6lgKyd6XX551YyHKuTKKzX75atR/UI4Uvw/26QkTar52bpVSxO++qoWGdm4sfh8cu9eYMIEbRaWkmI9kPx8Lbbjw+HQbN2bbwLPPw906mTx3JkzgTZt4GnUGGNS7sKRdbegdUsP7rpLKxAGUrLKoa/t20v/+9kmo7APdZALJwBA4EAWknGL400UxFV9s6/MTB2TT0LTUl6eFjZt2VIrHp5xBrB6tT43PV2zlw0bah81K0uXwrLCaFyc7sdOQYF+BTp1Atq31z6B6en+2x11lGZDnU79/iUn658TJgTXey0xUXsPNmtW9raAvu+ff9ZCJXPmBHcMAS02c8ghmtVzOPTr26aNZvdKWrBAK1W6XFqpslUr/2xdcjJw773BvW5FLVyo2VirQi0ZGZqRfvvtqh0DEVFYWEV60Xhjpo5igscj8sorIs2b66XhU07RBSx2hTGSkkQ++yzSo67ZPv9c5JhjtKfcxRdLzsp1ctJJehXfm4lJS9PCEj/8oFmd1FR93OkUGTnSYp+vv64Pulyl19T53vr1s8/UORwi48eX//0sXfpfWuJajBF3iexiYqIu6Tt40P7pdpk6t9s/o9GmjfW2KSke+fPP8g89WBkZIpdeWrw+sEkTXW8YyBlnBFfDyOXSTKivZ56xztQ5HPojb1c45dxzS2eJnE6RI46wLwCyaZPIG2/oOrrdu8t3XIK1f78u60xJ0febkiLSpYvIvn3BPT83VwvzPP20HveCgtKPl/gKljquzZvrn7Vq6XF44olQvzN/L72k3/tAn3k4soVERKECFkohiqAhQ+zOfrXKIEXGK6+UPvt0OETS0qRw7V8yY4bI44+LvPlm6ZPdzEyRqVP1Y9uxw2d/Ho9WH7ErIOJ7q1/ffy5byemXkyeX/z1dcIGIMbIBLS0Lu7jd+rbtWDV3dru1MbWvY4+1v1axfXv5hx6s/v39Ayy7io4i2vi7PD3lu3Qp/fzCQg207OJvl0vkxhv9X3fJEuvXdToDFz8JRmGhXo8YMkTk6qu1amSwrrnGP9BJTNQZwaFw/vnWx8rpFHn0UZ322rmz1trJygrNa9qZOLH4Ao3dzbcCJxFRNGNQRxRJ06bZly30iwwooD17RN56S8s52i4oC0J2tvXZnretQEVccUXgzJzv7Ygj7NdhxsfrOs1g7dypvRiKzqY/xfmShv2Wuz733MC7mjlTT7oDVr8UkaFDrYd+3HHlO2w7dmgAFExbg61brQ+ZMRrPWhkzpnxBndtd+vlXXFH2810urY65d6/IggX6nt54wz476HDoOr2K8Hg0cPJ+fY3R8T36aHDPtxuT01mx8fhq3dr+PZdcW+dyifTs6Z/pC4W//9Y1hgcPamsHu88tOVnbXBARxQq7oI5r6ojC4eyzgZNPLi5b6HDo2runn9aFPBSc774DmjcH7r4beOghXaxz2216flZeGzZYl+wrLPTvAB2MxYu1smWw5fSMAUaNsn/85Zd1nWYwRIC+fYHZs/87Fk3xDzwWv+ITErTnfSB9+wIrVuih2LlT1z35Hqq8PG2YbaVp0+CGnZWla9saNwaOPlrXafXv798su6TNm63vFwHWrrV+rGVLXfsWrJJ90//4A/jkE+s1Wb6vf8st2oj79NOBFi30+Nj0kYfHo+vQvv46+HF5vfQS8PnnuibM+9pZWcCIEdr3vSx2X9H8/Ir9KJX0ySf26zY9ntLLRLOz9fh+9VXlXrOkTZv0u9Spk67pa90aePJJ/Uy9a2WN0bWLTidw1VXAoEGhe32qQjk5+kuJiCwxqCMKB4cD+OILYOJE4LLLgKFDgR9/1DrzFJzsbODCC/XsNTNTo4rsbOD997UwiIj1f/iZmfr4vHmlo4WGDXUfVlq2LP/4Zs6035+XMcVnlJMnAyeeqOP3tjxISNAo4KmntOhOsL74Quvxl3j/PbEALbAZ8Sh9Bp+QoMFHZW3aZB98Bdul47LLgBkzivcjoif4555r/5xffrEuWOJw6OG0cuqpQIMG/oGdVUzvdgPPPFP872Dje4+neGwHDmjw8ttv+pFYtSoA9Kt50UVarCTYYGr6dOCBB6yPvcOhxzMQb0sGX8ZoMBqoNUFZXnpJgySrQjB2MjKA77+v+GuW5PEAp5wCLFumvxoyMoA9e4AHH9QCOIsW6e2LL4DRozWgHDWqcu+ZwuCXX4AjjtCLoikp2oslOzvSoyKKPlbpu2i8cfolUYR5PCIbNlR9zXQ7X3+tFUus5lC1batzuRwOLXqyeLHIN99oJQ9jdCpjcrJW1Fi6tHifF11kvThrxozyj++NN+zn6CUkiDz7rLY2WLLEv3b+zp0ib7+t+yjv8c3IsD0u/+IQOdExR5Li88Xt9kjTppY9zStk7177MvW9ewc3bLulh8ZYF+3weOxrDjkcWmTEzj//aN2ixES9de4ssmiRNpuvX19fs3lzkUmTSj9vyhQtjFPWlE279XaASKNGgZ/rdovcdltwx71tW/v9pKYGXoaZm2v/maWl6ZTFirKbzVzWzekUef75ir+uV3q61pyymuUeHy9yxx2Vfw2KgFWr/D9Up7PsOeRE1Ri4po6IKmzhwuLAyekUOeookTVrwjuGL7+0D+p8o4OkJPuz1wYNiksPZmWJXHKJbpucrItv3ntPH//kE5E779SqInv2lD2+3bvtzyh//jl0x2HzZpGbbhLp0EFLOt57r315P4dD5MUXZccOkfXr7Ss0VpRdTDxtWtnP/ecf+0DIGJH58/2fk5sbuK1fMPbvF9m1y/9+ux51OTki9erZByUulwaFgVpUllUE1XueWtby2pycwPtISdHgxs6rr9o/9+yzgzt+dv74I7jg1/eWnFy5ojp79oj06qVLYe1qDgHaq45i0LXXWn+wTmfgqzhE1ZhdUMfpl0QU2J49Oqfpr790yktODrB8OXDCCZZ91KrMKado0y8rvvPJcnPtx5aTo2vPAJ32OHEisGOHvqddu4ALLtBFOVdfDYwcqXO3WrcGliwJPL569XShU61auhbOe/vqK+D4462fk5+vc/3q19d5kYccog3oRKy337RJG5q98w6wapWuMRw50n7ap8cDXHklGjbUdXShnmb2/vs6VTIpSWdFpaUBL7wA9OtX9nMPOcS/b5mXMbomzYrdc9q3D27MtWrp4fZlt/YtKQn44Qf9CiQn67q/evWAjz8GZs3Sj2DbNvuPGNAfG2Os+x+WfJ3ly60fEwFefDHw8ltj9Ktm1/YQ0LHa2bnT/rFgHHJI8MtJAT3ejRvrdNJGjSr2mjt26PrNX3/Vaa52y63cbp1aSjEmL0/nP1t9sImJwLffAuPGlf27maimsIr0ovHGTB1RhLzyinW5vNRUkU8/De9YpkzRsSQlacomKal81Sa96YxJkzSlcf/9Io0b6/y4O+/UUnlnnmn9vMMPD26Mubkis2bpPMecHPvtPB6Rk07yfx2HQ+Suu6yfc801gdMRVvsKlLoJkT17dJZUbm75njd8uPWwTzvNf9s//rCvYhgXp8nL8eMD9+CrDI9HZPlynbJpVa1x2bLA0w9TUjT5a9fbz+XS2bkimih+7DGRhg01k9WqVeDpnUlJNv0SfVxxhf0+7ryz8sfokkuC6wUIaIXUwsLKvd5pp5X9Ok6nSPv22oqEYsiGDTpdPtDv95I/FHXq6A8hUQ0ATr8kogq5557KnUmG2tat2s7g0Ue1YVygeW924968WaRrV50a6XsGGOjscOvW0L2PH36wP2GJj9eTGl+tWpXvvbZuHfo5lyE2YoQeWmM0OLvggtK9y5Yt0+UzZbX+czo1cEpJ0UMbCWvX6nmo3fj279fA0HfpZVKSSJ8+xfsZNCj44CglRVsjBPMxf/edfQN1qymp5ZWdLXLVVfp+XC49z7a6BuFy6edeGYWFga9vpKSIdOok8uST5esMQlHiuOPsf+jt7ne5qu6qDlEUsQvqOP2SiAI77jjrOV0OB3DsseEfT9OmWjV02DBg4EBtF1FyXpsxOjUnKcn/uUlJWjpwxQpg9Wr/6ZxWZRW9ROzn6FXEzz/bz1crKAAOO0znMpbUpIn19gkJ/qUdXa6YKO13771a0HTnTq1W+MknxR/nkiVA797AtGmB2xwA+tFlZOjtvPPCOzPYq107LWrqdpe+3+nU6aRt2uiPTPPmWo3T6dSv6jnn6MxdAFi/XtscBFvcb9cu4NFHg/uYTztNC8h6x+dw6I/E229bT0ktL6dTp+Tu2aPtJXbt0kKFJY9HQgJQty5w3XWVf71Abr1VC8I+9ljwnUEoSuzfDyxcaF+m1U5Ojn2fFaIagEEdEQXWv78umPGVnw/Urq1/93i0lvp992nzrX/+Cd/4Jk8G7rgDqFNHz5D79tUTgquv1jPWxEQNeI46ShcdPfGE9pQrb0nsI4+s+OIfK40aBW6elpenY502rfi+++/3jxiSkjSwXbECuOQSjSz69dOFYGefHbrxViFjNKhwOkvff//9WvZfpHz7EwldmfzyOvFEYMIEoFkz/eo5nbokaO1aDXaysoA1a7Ts/7vvak+3KVN0rR+ggYjdukFfbdv6H7NAjAHGjtWlSPfco8HgihXANdeU/30Gkpys7z8uDnjtNeD11/XHr1Ur4OabNVj3/uqoKIdDexxaneMnJuqvBIpRgXrR1a9v/3tTxL6RJVENYKS8/1tGSPfu3WXRokWRHgZRzSOigcL69aXvNwYYMEBTK/36AXPn6hl4UpKecU2ZApx1VmTG7JWZqemCJk1KnymPG6dBX1npH6+EBM3sldW1uzz279esY1ldrU84AZgzp/jfL72k6Ye4OE1H9e2rgW1qaujGFiVq1QIOHiz/89LSgPHjA/e7C6SgQBOpOTl6+AMVH/G1fr32oM/L09o+jzyiLSmtdOgA/Pln6fv++AM45piyvxZxccBnn+k1l3DJzdWM4urVQMeO+uMfKADNy9Nt69TR7GSobdkC9OwJ7N2rYzNGr3n8+CPQvXvoXy+iduzQg5+frx96RXppxorNm/ULlplZ+v6EBE3Bjh9v3eE+Pl5/KIKp1EQUw4wxi0XE77dcxII6Y8yZAF4BEAfgHREZHmh7BnVEEXLggM4Vs5oqGBenZ7zp6f4BUq1aOqcu2LRDOGVlaQnDQNMtvRITNVtWFeXzFizQuXd79thv066dpnlKysrS+xo10hKC1dRhh/m/9ZLS0jRw8P0Y3W5g+/bg4txZs7QA6caNwOGHa4bp44/1WoYxGuC99ZY2Sg9k927NDn3yif7b49Fz0Nxc+0yjMZqU8M029ekDzJ8feArps89qYdZw2bZNp47u26c/7ikp+mvh11+tE9gTJuj5t8ejvzq6d9frPFYVPL1FDhcs0GPRubNeDwpmtnN2tgbRq1drf+qBA61nXse0SZOAa6/Vi2Xe37PDhunMiFhXUKAlUJcu1YtmAwYAnToBW7f6/+AYoz+cqak6C8H3/5wjjgB+/z3wDAiiasAuqKuywiaBbtBAbj2AQwEkAlgGoGOg57BQClGYLF8ucsMN2rjq1Ve1iZRdH7RAt7Q0kZ9+ivS7sTdnjn+lBZdLK1Kmpeli/FattKNxVfJ4tA+gVWWMhITgu1JXQ2PH+hcVcThEmjYVef11rWg4aJBWiDRGD5fLJTJxYnD7Hz/evl+879ciUFvGTz4pf70eQAuJWBU4OXhQK1V6i7zaPTecNSEGDvSvKxQfL3LWWVogpaT58/2Pa3y8SPfu/vv97jstpFvyfbrdWrFy9+7wvLeotnCh/4H3filXroz06MovL09/mDZs0K7ztWoV//+SkqIlbq36fXpvLVvqD82yZSLHHKPHoXZtLeiVkRHhN0cUHoim6pcAegH4rsS/HwTwYKDnMKgjCoNPP9UzKm+wk5CgZ9HlKaPvvaWmisybF/ox5uaK7NtX+mz4779FHn9c5JZbRL7+Ovha6Rs2iAwZom0NjjpKZMIE3e+mTSKff651+iti/XqRoUNFOnfWqGPhwrKf8/77pc+EExO1Ufq//1ZsDFHE4xH580+RBQvK1/bA49G2Bykpep7ndGrrAm/veO8233+vXSCefFIPfTAKCrRpeDBf5fh4kQcesN7P7t1lV6oM1DD92mvtK1fm52uAatXU2xgtABsOHo91XOG9paTo5+Q1eLD1di6Xfg+8tm+3D6oTEkQuuyw87y9qfP65SM+eGrhceaV+oe0OfFycyMMPR3rE9nbs0L4c99+v/UhE9CpN7drFH7rVD4Yxgft3JCaGplQrUQyLtqDuAuiUS++/LwcwymK7oQAWAVjUokWLqjs6RKRnynaNwII5Q/W9NWxo3dCrorKyRK6/Xs/sExJEDj1U5OmnRbp1+//27ju8qbL9A/j3STqStJQle4gbQXFQFQdOFBcuxPm6Ny7c81Vft+Lee++JqCgqouJmKUNUEFSWgCije+T5/fGlv6bNOWnSZvf7ua5e0JPk5ElO2p773M9z3w0Dz8JCa4cM4RlxrGpqeDLl8/EKst/PWvOx1ET/6SeehdedjBnDk5hx45p+7Oefs37/1ltbe8kl1i5dGvtrSDO//WZtv358C4qK+PXaa7Hto7zc2nnz4puZWrgw+rYBAGN0J08/Hbk/ncdjbe/e7ufmBQWRWzCMHu3+WJ8vPEvWWHk5s2EffljfKmL8eGsHDGAmcMMNrX3uucj7CAabbgcZCDAAXbiQrQTcfnUcckh9YHfPPRyD2z79/sjjyiq33dZwRkRTPTw8HmsvuyzVo3Z2xRXhfyd22CG6tHhTX7m5ajoorV5GBnWhX8rUiSTY9OnOKYFYvwoLeeb+7bfxHd9hh0U/x62ggFeFY3X77c5NxI4+Ovp9HHSQc+BbN22oFamt5ctufH4aCFg7c2Zqx1ZSEv3HqbDQ2nffdd7PY49FPlf1+/lab7zReRazMdaeeab7OCdMcA+o/H4m19189FF9IF1UxNdx443h4w0ErH344cjv1/DhkbN1dfvx+SIn9uuucbz7LjONkfaXn9/0ccwKy5ZFf7Es9M2eMiXVIw/35ZdNB6Qt+crJsXaPPWJL+YtkGbegLlUtDRYDCK2F1XPdNhFJlaKi8L5tsfD7gSOOAB55BFiyhGXp4mXJEi6mj6awCcCqaS+8EPvz3H9/eNnBykrg1VdZlGD69Kb38cUXPP1o7I8/UldnP0W+/JKVCRvXM6isBB56KDVjqlNQwA4QoS0O3e63007u3SEOOMC9iGpeHtsGbLEFe9Q5FfCoa6voZo89WD3SjVMRQIC1dw45hNVD675KSjiexh/xsjJuj1QM9sEHWcEyUiXQsjL+iEaqSG8t73fyyXxtBQXO9/N6WTOjVbjlFuffGW5yc4GzzgIGDkzcmJrr7rujryrsJlIvupoaVtR54omWPYdIFkpVUDcZwCbGmA2MMXkAjgIwNkVjERGAlcf69m1+5bCrrmLj12OPdT9Ta64//oi9pF0sDbzqrF3rvD0YZCPwbbdl1cx33nHfR8eO7rcdfDBfSyuxYoXz9tpa4Kmn6htup8qDDwKHH17fhaNOXS/3nXdmY+733294e6ju3YHbb2dwmJPD89HcXLZCmDOHve7LyoB993UOdnw+4Pjj3cdoDK815OY637777s7b33jDebtb7LB6tfvHH2CFy19+YXPxWFo8uCkvZyXMIUPCA+ucHFYhvffelj9PRvj88+jv6/WyhckddyRuPC3xzz8t30dTAW5ZGT+IItJASoI6a20NgHMAjAcwB8Br1trZqRiLiIR45x2mFAoL68/cIl01rdOpE4O6aO7bHJttFrm+e2MFBcBpp8X+PEOGuJ+91/nnH+Coo3im7+Tii91TL6WlPMs/7zxm/n74IfYxZpAdd2S5eieVlcyUff99cscUyudj0Pbjj+xH/+yzwBlnADfcwIrqX34JHH1006X1zz2XDbWvvJIN07/6ignbb79lcFJUBGywATB8OAOYggL+6/PxMU0lXIYPZ7Yw9FpJQQFw3HH80XCyZo1zFxI3BQVNt4DIzWUQ/PjjbBvREjU17Hry5ptswj5kCBuUDx/ONpK//AJ07dqy58gY660X3f3y8/nhHD48seNpiRNOcP87kJ8fv3YD0fS7EGltnOZkpuOX1tSJJEkwaO0337AS27ffsgRdpBLTgYC1d92V+HGNGtV0tYa6hTjnnNO89Wvz51vboUPk6g11X1tu6byPYJDVJ9we5/Fw/YzHw/cutGxgFrr00sgFSQ47LD7P8+ef1o4dy44cP/5o7f33syCLWyGR6mprL7ywfh1Yhw5cHxcvY8c6r127/HIWV3noIWt//z36/VVWWvvoo9buuqu1e+/NtXSRPuLTpzuv9fN6w5c81bWJuO226KvCf/qptXvuyQKtkZZQOS0V83pZN0PWOfHE6NaT7b13qkfatMpKVv1tPPbOnfnDefLJXGgbS5Wixl8FBdY++WSqX6lIyiCdCqU050tBnUiK3HILz3qdzs7y86297rrEFgCZMIGl+qIpJLD++qzo0KULSy4+9VTsY/vrL2uvvtrajTeOXPEhEHDfx047RX+C4vMxIslSwSA/Im4vf8MNwx+zahWDsjPOsPaRR6xdu7bh7RUV1l55JVsSBAKsLpmXxzo/dUGLz8fvO3RgkNdYXUDX+JC+9VZ8XvfWWzu/3jZtoivMWlbGmhMzZzb/+sQmm8RWf8Pv5/l4UxU1Qx12mPv+2rdnV5DDDuMx8XhY52LDDa1dtCj215S1+vWL7gBlShXwqipr773X2r59+Xv0v/+tL71ax+2qx/bbR6485PGwaWI8KyuLhPj9d2vPO8/aHXdkEau5c1M9onAK6kQkdu+955yl69CBmbyKisQ+/9dfR18G26mfXk4OfztHEgwy7bHzzjxpGjbM2mnTGGhFKo+4xRbu+7z22ugrwPn9jFyy2LPPur/8vn0b3nfuXGs7dqy/kO/3s41gaBAwbFhsF/o32KBhYFRR4f6x2mqr6F/XggVMtF57rbVTpza8rW1b5/3n5zfdVPupp/hjV1TEf/v143PFMq62bZtXhLCggJnEaB11lPN+8vKsffVVtlIIBOqDS4+HVThTXf005ebNY6XcgoLo+4DuuWeqRx1fr7/OCN8Y/pA/8giveNx5J1PAjV9/To61DzyQ6lFLFpsxgxfe6iYF5eTwRzTexbxbSkGdiMRuzz3dA5FYzjKba8iQ2M9KnYK9Zcvcn+Pii8ODN2OsPfdcTvFxquMeCPBKs5tlyxj4Nn6cU9qksDC2s+gM9PbbzuX8ATaqDrXHHs73GzaMt8+ZE/vMrYKChkHEX3+5x+sdO0b3mp55huPIy6ufSRs663fHHZ3336FDwyRDebm1P//M7KS11n7/fXjA6fEw4RFtxu6UU1pWVX7EiOiex1q2TXC67tOuHYNnt5nIQ4dG/xxZZ86c6PtphP7OidTQMJO5fbDffJNXNAoKrC0utvaTT8Lvs2YN53gfeij7crSytjESX26nPNtum+qRNaSgTkRit+WWzr/h2rThFMV+/XiF9cQTEzOFsFu35p+Zhn6NHcumaStXNpz7tnix+/q5vDyesS5dynWFdamXDTeM3ByszoIF1h5xBOeg9erF+X5O0Yjfb+0//8T/vUsjJSXOJ/5+v7WffVZ/v5oa92DEGN7n9deZwYrl8BcWMvka+jwdOzrfd8gQ99cxebK1Bx7I9WdO8XkgYO0XX/C+n38efrgDAa6lq3P77RxbYSE/hiee6H4do7DQ2u++i+79bteu+T8qOTnWXnBBdM9jLc+h666L+P381VBYyNe/erV7b7s2baJ/jliUl1v7yivW3n03A+S0s3x55H6gXm/9B8LnY8qgZ08GONLQxInhvzDatau/QiISI7fTAWPSa8avgjoRid3llzv/lvN4GqZevF4ucIqUEWsOt8tmsX5dcgnHV7fw6tprGeS9+WbktM/WWzfMSLb0KvADD/BEraCAJ26BAKextgLvv8+XGwjwMPj91l50UcP71NZGXgP200/uBUAifXXuHP4H+fHHnZf0TJ7sPP4vvmg4jdDtD//IkfWPmTiRCYZAgJm2F16ov+2ll8KfPyfHff9FRXwPm/Lrr7H3sQ798vuZOYzV3LkMWF94oX4NZFWVe0KqT5/Yn6MpM2cyWK+LiQIBznCMZg1j0lx6qfuVi0DA2uOOs/b5560tLeXAV61S9smNWwGvvfZK9cgkQ7ld7PP70+vHUEGdiMRuwoToKk4CPIu66qr4Pv+kSc5n8Dk50Y/L63VOmVx3HfcfaRqUMXzsgw/G7zX99RcXTb3wQqu7ovz336wweffd7oGD2x/VvDx+HK3l8sdoCpTm5/O879NPnZ9rzBhrt9mGz7n33u4BnbXWDhzY9PPVzdqNRv/+0X186758vqbX4lnLAjPR/mjUnazUZdjateNU2Xg66yznH794LY2qrmYMtN9+zuf4gUB8f3xbzKkyZOhBnjEj1SPMDLNnR/6dL9IM//1v+CmHzxf97/VkUVAnIrFZsICXvGM589x55/iPY/x4azffnGfM663HwPHXX609++ymz149HvcpnG3aMJXQp090Z9R//BH/1yZhLr3UvdDqypW8z+rVTGjk5fH8bZttGDwMGcJM2SOPWHv++SzRv2RJfMYVTaDk8fDjGs00Hbfg1e0c9cYboxvnM8+4JzCGDAl/HT6ftQccwKmKVVUte4+cVFRYe/TRPH51BQgOPDA+Sf2aGiZlInVcAZhwTxuRZh9st12qR5c5fvgh8g+MSDNUVXG1RX4+V1z4fFyuGUtF4GRQUCcisRk1yn1BjNsf0hNOSNx4Gs99+P13niWGRgA+H9e8de3K1Monn7ivX8nNZaZswQKueWsqqLv33sS9Nvl/f//NODz0o1dQwCuojdXUJL4Aa52uXaP7McjNZTGU0EzU778z2AudyXvAAdFPk9xnn/rHffWVtcccwwDtwQc5Sy/UqlXu6xfPOMO9YM2WWya29tHYsbxG1KYNv+LxIzVmTHTXnSIVqk269993PkCdO7Poh0QnGHRP1ys4lhZatIinD7H0Ek0mt6DOk7Ku5yKSPsaPB/bZB9hyS+Cyy4AVK4AffgBqaqLfR34+cNFFCRsijGn4/frrA998A+y9N+D3A127AmedxXGsXg38/DPwn/8AvXo5769dO6BNG6BPH+C334AbbgB693Z/fmvj9Uokgo4dgZdeAnbYAejUCdh2W+CZZ4D//S/8vl4vD3cyXHopEAg0fb/qauCff3j/p54CRowA+vYFjjgC2Hxz4LDDgMpK4NZbgYICwBPyV7jxRxzgc950E///wAP8uL/8MvDJJ8AllwCDBgFlZfX3b9sWGDOGH+2iIn4FAhzLrFlAVZXzuGfNAnbaKbYf+WiVl/NHsaQEWLuWXxUVwBVXANOnN3+/777LfUbi9wPHH9/854i7/fcHrr2WA2vblv/usAMPQJs2qR5d5jAGeO658O15ecAbbyR/PJJVevQA9tqLpxkZxSnSS8cvZepEEuSuuxpOIs/LY6pk5Mjo5pzl57Mc4LhxqX0dVVXObQR8vvB1c4FAfRuBBQvYrLyuNr1bpi6bpl8uWNCw4fHmm7NbdYoFg5w26fczU5efz68332T1yk8+aXky48cfrT31VK6hGz06+mWNwSAbnvv90a9Za9s2fD1ZTo61J5/Mff70Ewuk9unDVg5PP81WiYWFLIzi91v76KO87+rVzjV93NaMlZezzeSYMfXv2SmnNN0SrVMnjiue3n7buWKpx9OytSqXXBJ5MkFhobU77JB+U6estTwokyZxKrk03/z51h5+OGvOX3BBfZUekSwGTb8UkTBr1zqfKebn82wrUu34nBzOn1q4MPVlocrKrB0wwD3oPPVUrvcrKuI8s7feqn/s+us7P66uwqfPx+oT2aKiwnnaUl5eg7PfefOsPf54Nu7ebTc2kU6EVavYpPqVV6x991339VE+X32Q1NzD8dZbDILqAhu/n4c/mgIkFRVsOVBXVTHaftFuX241hYJBNrr96KP6YGzlSmufeML9xzHantSzZ0dXObRnT1YibamKCrZt6N7dfarpiSc2f/8//+zeJWTUKH6e0qkMuYhIPCioE5FwX3/tfqa47bbWzprFM/rGt3m91r72WnRnw8nQ1Pq/0093ftz337s/pqiIqZw0yGDF1dVXu7/mCy+0ds4cO/ece2yRZ631oKZBRujxx+M7lDff5H7r1llFGyiF9oOLVnW1cyI3P9/ayy5r+vGnnhp70/NIXwUF7OUWSUkJG4HXtSxz2o8x4Q3cI/n0U2bjIo2tTZvY39/GgkFrd901cnHZggKutatTVcVgdswYa//9N7rneeEFfh6KijjuTp3StD+diEicuAV1WlMn0pp17sxFQE569AD69weGDw9fTFRby0VC3boB22zD9SCp9PTT7ouBCgo4Od7J++9H3u/FFwMbbNCysaWbb75xv+3uu4F+/XDdAx1QGvQhCO//31RWxjVcbh+XWC1bxnVWZWX166xqa6N7bHk5cN994dvLyoDHHweOOw64/npg8eL62375heu4Gqus5Bq0SEpLgRde4PNGy+8HttjC/fayMuDJJ+u/f/VVYMMNuU6wTx8+39FHA2++yTE6jb3uec4+O/px7bEH8PvvwMYbN1zPF8oY4N9/o9+nk4kTgWnT3Mft9QJ77gkccAC//+47Los9/HCugevenceyKcceCyxfDrz2GvDee8CSJcB227Vs7CIimUhBnUhrttFGwIAB4RUacnKACy/k/59+umElhlDV1SyoMngwsGpVIkcamduZI8Cz10MPdb6tbVvn6hQAsPXWLR5WWurb1/22dUmUL7AbapETdnN1NfDnn/EZxptvNv+x1vJEPtTffwObbAKccw4Doptv5kuti2FXr3b/GLdrF/n5/v3X/WPiZL31eL3gxRcBn8/9NdQFia+/Dpx8MrBgARAMAn/8AZx+OguBBIPhj/V4WADF52MRlcGDox8bwGs0U6YwoHJ6XVVVwC67xLbPxr75xv39rvP883wtFRXA0KEsMLNmDb/Ky4Hzz6+/XhQM8hhXVobvp6CAj991V/7qird584Cvv26iKMtvvwEjR7LazLnnMnIWEUkiBXUirV2/fuHbamp4Vnzffe7l8kJVVfFMOlX23ts57dCnD/DVV0BurvPjhg9ntbTGjAHuvTeuQ0wbN9zgnqJZpzsWO26vqWF1yngoK2t+pUW/Hzj44Prvy8sZgy9ZUv9xrazkSfgJJzCAeuIJ9/1tuy2zZvPmOd/erZt75UuvN3xbSQmrpg0YAEye7BxoFBQwEwewCmTjAChSVrCwkJm9P/9kVsta5/utXcuqlzfeyGqZofdr25bB5Dbb1L82Y/j/G24AOnRwf/5odO/O4+TG660//h9+yGxoYxUVHP/rrwM9e3LyQJs2LBY5frz7646XFSuAHXfkcdxvP05suPtuhzuOH8/fo48+ymj20Uf5oB9/TOwARURCOc3JTMcvrakTSQC3ohmhC45ycqLrV3fBBal7HfPns5tz3aKnuqoas2c3/dhHHuHrzM3loq7cXGvvuSfhQ26OYNDa775jFciSkhbs6Isv+P64HMt3MMwGUNJgsy+/1h51VLxeCQ+N0xq1vLzI/dv8fms326xhkbvLLnO/v8/HIoOR1uv5/VyX5fOx6KtT3Z9nn21YZMTjcd9nmzYs/hL62LqKngCrMh56aH0xkliLrvTtW18ltK5Y7SuvNBzvDz9Y264d160Zw+fcZZfwSpDl5aywuffeXJvX1Dq/aK1Zw+d3ew09etTf96KL3O+3557OxV1ycqwdPDixfQp32SX8V18g0Kho0IQJ7lVzd9stcYMTkVYLKpQiImFWrIjujNLj4RlvpPvefntqX8vKlRzDiBHW3nijtcuWRf/YhQtZUvG++6z988/EjbEFZs9uWO4+tCtDsy1dau3EiY7R1X0427bBaluINTbfVNgjjgiGNbpuqYsv5uswhl8FBdZuuqnzxysnh8HMXXeFVy3v3Nn9Y5mXx3YB0QZMBQUs4OJk/HgGEr16sRXBSSc5tzfIzWU7gVC//soaNWefzWIgoYHjhhvGFtTtuGP4IQsEGOxby307vY9+v7W33Ra/4xdq9mw2VC8qYsXUBx6wdvp0tmtwC7anTuVjhw93f61uxWnr9pGo17NggXuRl733Xnen6mpr27d3H2BubmIGJyKtmoI6EQkXDDJKiOZMctdd2ejKLY1y1lmpfjVZq6aG2ZjGb73fzxPnFjvkkPB0iDG2Ir/Izul3mF05c3EcnsTZpEnWnnEGC5R+9hkzZU6JjzZtGlZKDBUpI7TzzgzsYgma2rYND8qczJ/vnEUyhonj33+P7j145ZXw/QQCDB5Dr6MYw8+BW7Cx667143Kr1Nm3b3RjisX8+Tw+oZ/PQIDFVKdPdx6Lx8OWGdaysqjTrxWvt+lKnYl4PdZaO3mye2HgLbe01n78sbXbbBN5cB06JGZwItKquQV1WlMn0poZA1x9dXT3LSpiNYLCQufbG1eukLj54guu07K24faqKotHL57LRWG9egGnngosXBj7E7z2GnDddSwq06MHyymOH4/8WVPRd/ab6LBF97i8Die77AI88giXIe22G3DKKc7FRTweLp10csghzmvb8vO59sytWImb1atZ3PXRRyPfb4MNWHGx8XNby7pB0f5oHXkkKz2uvz5/JHv0YNGX5cvr952fD5x4Iit1Or1WAJg/n//GUtQlkqoq4OGHWftj992Bl15yLtxy221cAxj6+SwrAx56iOsUnZatBoP1RXdOPNH5GAUCLH7SxBLQhNhiC+fXmpcH7L/+bC7qnD7dfQceD3DWWYkboIhIIwrqRFq7yy4DDjww8plTQQHrxO+8s3PhlIICYNiwxI2xlfvnH+cT9dpag2UTZvLkctEi4NlnWfli6dLYnsDrZWWRlSvZB+Djj9lfYOON4/MCYrDttqzR4/OxKEabNqxOOW6ce3B2660szFFQwO9zc/n/yZMZIJ10Uvhj8/Pd6+cADEouu6zpOkH9+jkXQqmtZf2MaB1zDAsm1tYCgwYBP//MQ1L3/F4vsO++wFZbOX8WjKkv5b/++kDv3uH38ftZZTMatbUMoi++mLU/Pv+cFTlPPDH8vt9841z0Jj+fx8+pYqXfz9cD8CPbtm34fS6/nEVb3IrU+P3O44kHnw+4886Gz52fD3TsaHHRl4c2Xdpz0CDg2msTMzgRESdO6bt0/NL0S5EECgbZlfi006zdd18WDqmrWFFQYO3BB3MOoLXWXnklt4XOs9p668RWLGjlli1znnJXgLX2WRzXcGNenrWXXBLbE1x6qfP8v0mTEvOCorB8Oacljh0b3UerpMTaxx7jVL477+QSyzplZVwH5ffXr0fcbTfuP1JD8UDA2lmzIj/v2rXu0zs32ST21/3vv+61i7bdlvcZPTr8cBUUWPvjj/X7+fFHTkstLORUx8LC2AqLvPuu88xsv9/amTMb3veII5ynzPp81i5ZwrWEob8y8vM5tbSuwfjo0c7HoUMHLlv78UdOo61be1n3enfeObzwS7x99pm1Bx1k7cCB1l51lbUrflgUecplfj5/X9ZVwRERiTO4TL80tvF8njRVXFxsp0yZkuphiLQOCxdyrtU///By+u67N0wPjBsHPPgg56kdeSSn/UWqXy4tdsMNnOZWWhoE4EEApdgcP+Er7IJ8NEonDRzIRmTRKCtjYzWnGvo9ewIff4x/OvfF888zk7TTTpzuGCnLla5mz+ZX376sOA9wyuJuuzHR6cQYlrJ/5BG+bieHH85pmKEZqUAAGD2arctisWABp/45JYJ69Kgf5wsvsEfdX38xQ3fbbcx4hSopYTuAJUuYONpzz+inZp5/vnODd58PuOOOhg3Pp0/nNNrQMft87IP3xhuMdt56i+0A/vkHOOggNrKva48xcCAblTfWpg2bmA8cyO/XruXrWbyYrQb23DMFUzPHjm3YTyNUQQFTmnUDFhFJAGPMVGttcdh2BXUiIpnhk0+Ahw6fgFWrDY7AqzgRz8KHRnPbjGGU8dpr0e10/nxGOE6NwgBMyxuEPXK+QLXNRXk5l1T26cNmzG3atOz1lJSwAfXEiVyfduaZ3He81oRF6/33uYauqRl1TzzBNX+NrV7NgO+777jmqrKS0xzvvz/2oKO2FujalY22Q3m9wLHHcoZtMhxyCPDOO+HbvV5e7zniiIbbx4/nErJFi3if445jq8dorvUMHgx8+WX49roptJtv3qyXkBh33sk5qU4GD+YCWBGRBFJQJyKSDYYNY1rITSDAKGn77ZmimT2b2zbbjBm5xioquN0lqNscP+FnNDyrzs8HLrgAuOWW5r+Mf/4BiouBZcsYTOXksDCFtfVrpUaPdl9PFW+PPMI1XDU1rm8F8vI4VrdCJb/+CvzxB2PkLl2aP5aXX2byuy7IzM1lMD11KoPfZNhoo/rCK40tXcrAszFrGeAGAs7FUdy8/DJw2mkN33djuKTzl1+SH+RHdOKJ7pH16NHuAZ+ISJy4BXUqlCIikkl23939trw8nnAOHMhUUZ8+nD67yy6cQ7jLLgz0Qvl8PBF1iJ4Wozt+R5+w7ZWVPBFviZtv5jS6usClpqY+qCsrA556yn26YyKceSarTT73nHvQVlMTeVbrppuyuEhLAjoAOPpoZr4OPBDo3x844wzgxx+TF9AB7lnLvDxmE50Yw6I2sQR0AHDUUcB//sOPYmEhC+126QK8+26aBXQAo3YnHg8/ACIiKaKgTkQkU4wZw2yAE6+X898OP5z3eflloLq6vi67tcBXXzEobFyr/dprmXZrVMYxBzWwcD6rbumaujffjFxZsqICmDQJ+Omnlj1PLPLyuE7LbQKLx5O8IGOXXRjUzJrFaZy9eiXneevst59zVc+uXVlpNJ6MYaZ01izggQeAV17hst7NNovv88TFdts5f/hzc+sXaoqIpICCOhGRTPDVV1xUtWyZ8+0+H6tbAIwCKiqc77d0KaOlUMawekijHoRdsBxbYgYMGqZm/H5OD2yJuvYDkVRWsrhGMlcJtGsHDBnifFtRUfxrYFgLfPYZX+eYMYzD4+HLL4ERI7jM6/bbgTVrYnv89dcD7dvXt4LwepnMffLJxAW2G20EnHCCe0CZFs47jz8AoW+C38+0ap8+KRuWiIiCOhGRTHDjje5z4jbdFPjoo/r5eZHO4K0Nb1D+88/AoYeyY3aIZeiMf9EBgAFgAVh4vaw8eMEFzXwd65x9dtPr5axllcfHH2/Zc8XqvfdYgbLuvN3j4Xn7O++4T81sjtJSVhMdNozr+Y4/noGNW//4sjLG7UVFXNe4777A3Lnh93v4YWDoUGZDv/ySfeW33ZZtCO+6i1M6N9uMFVXdPlI9ezJLesUVwB57sEDMlCnuAW+r0bMnqwTttRdTu+3bA6NGsXqMiEgKqVCKiEgm2Hhj4LffwrcXFgLffssz9TrDhrGko9Pvd7+fNehD57adfTbw2GNhHaT3wzh8gr1Qg/pFUvn5wFVXAf/9b8teTjDIpuCvvcZAya04CcDz5pUrk7u+ylpWs5w4kXVkRoxgFi+eLruMbQNCk6peL7NrEyeG33/IECZs6+5vDDOeb73FQG/bbTmltXPn8GDN5+MUztB1jF4vm37ffz9fXya2qRARaW1U/VJEJJMddBAXWTUWCLDCR+h8xl9/5dqfxhm7/Hz22Hr11Ybb99kH+PjjBptKUIAO+AfVCK960asX8OefzX0hDf32G/D994wnjz/e/X7XXAP873/uty9ZwmWEq1fz5ey8c+qKbKxaxWRO27bMarq1NejenbNhG8vNZXXQ0NmwM2ey15xbZs3vZ+B22WUsQuOUrPV4wpdTAnzcNtswkMzPb/LluSorYx+5uXO5vOyQQ2IvmiIiIpG5BXXpOmtdRETqvPwy8OGH4dv9fuDSS8MXqG26KVsZ3HIL8PbbPMPv3Jnrgc49N3w/e+3FeXohDcirkOdSIsW5T3lzbbQRvwBOB3SaTghwXdgFFzhny959FzjySAYsVVWcYnjAAXzbmtOcesUKTrWsruZSqViKlNx/Pw9JXh6zfW3bcmasU6+1RonRBhoHXz/9FHnqZ3k5v667zj2YdbuGW1EBzJjByp+nneb+HJH8/jtbVKxZw/fN52Oz9G+/de6kISIi8aU1dSIi6aykhNUjnCpoHHssU1hOevYEHnyQKaySEjYdGzXKOTI4/XRGSyHz7zoEKrFphxVhd83N5fK7RLj9dvcgLD+fZf0bKy8HjjmG/1ZWMnApLeXs0zFjYh/DK68A66/PtWsXXcT4+O67o3vsN99wbVxFBYObtWs53XGffcKDtNmzgU6dnPfTpQunU4babDP3VgKhamuZ4Wt8mPPz64ueOCktbVmbigMO4BTZuo9pRQU/clndtm3VKr5pL73E1KqISAopqBMRSWcffuheEvHbb+Mzx7B9e2DaNJa07NmT6/PuvhvPfNgNbdrUBwMFBSxpf+ONLX9KJ4ccwmmTTqqqnEvpf/GFcyBYWsrMUyxWrGB7v/JyTiUsL2dwctVV0bVWeOih8CymtTzf//rr+m3jxrE3/Jw5zvtZtIiBYOhUy623ZuXNpta9VVcz8dq3L49XURETujfcEFbcNEzjQDJa//7r/P5YGz7TN2u8/jo/kKefzkaCPXqwqo+ISIooqBMRSWduzY4B4K+/4vc8XbsyKlm4kA3DTj8dA7fz4NdfgauvZnPoO+7gyXvnzvF72sbuuCO8KmZuLtd8bbJJ+P0jTUmMtVLlO+84B4gVFSxo0pSVK52nOJaVcXYrwIzdySdzW6Ql7RMnsn5NqHHjWNAkksJCYPhwrsH7+mvOvv3rL+CSS9jJIrSeTqiCAsYmzfHtt+63RZpimrH++ovZ8/JyZsFLSvghOf1099KlIimyYgUvFGVICQ1pAQV1IiLpbI89YAFMwi64DtfgAZyNv9GRtzlFOXHWtSszVc8/D5x5ZtPZnpbafnvgqaeADh34XPn57Jc+dqzz/QcPdk5WFhQw8/fjj9GvAayudj7xsZb92ZqqWn/YYe63vfEG/12wgNMym1JTw5l9oQ3aCwuBF1/klEandhB+P4O2Qw7hezJgAJup12XgNtuM8fr48Xx/i4rw/5nYc89lf7jmiDStM9lN05Oi7mA2FgyynKtIGli4kDMfevbkn4pNNol8AUYyn6pfiohE4/vvWQVj8WIuIDr9dJ4RJ1htjcVhRR9jQvlOKEMAPlTAgyDe9R6KPcZfzrl2WaimBpg3jzNDu3SJfN9332VAVZcV8nj4mJUrGXDU1rJmjFONmFCLFvHEx61ve2EhC436/c63r1jhnsUsLGQwt2IFA53KyshjAZihXLGCxVZCWcsg9/77WaDEGL5Pxx/PGbSRgqw61dXAJ59wauhuu/HEr27fkyczK1hYyH02lZl98kn3ZvSPPsoflaxy88280tGYx8MSrVdfnfwxiYSorWUXnIULG67FLSxkceRu3VI3Nmk5t+qXytSJiPzxB9MiEyc613x/9ll2YH7xRd7nqquArbZi/fwEe+llgwkYglIUwsKDcgRQikIcnjcWNbtlZ0AHADk5XBfWVEBnLdeLhWbrgkG2CqiqYsGS0lIWMPngg8j76tmTwZ9bsZbaWgY8bjp2dI/z64KmTp2AXXbh62tK797h69x++IHr7Y47jlm/Sy7hSdr33wPnnBNdQAcwYNxvP9baqRtbMAgccQQbov/vf9x3166stxPJRx+5P0cSrntEVFkJfP45g9+4cZv2bC3LpabK2LEsQdqlC8fhVFlIWoUJE3hRq3FxpZoazoSQ7KSgTkRaL2u5cKlvXy4oOvhgoE8f4IEH2Iz7t9+Ytjn33IaLoCoreUbtlp6Io6efBkrLw39V1+T68f33CX/6tPf11yw44lZLpk5ZGXDbbU3vb9QoxutOmprG6fGwnUHjqZGBQMMeey+/zOeoK2SSk8P1f3XBpNfLxzz6aMNgdc4cTjf95BNm/ebPBy68ELj22qZfVzTGjGEj89ATQWsZLEZa2tmrl3MBF5+v6aA8kc45h1nV3XcHNtiAwWtclqGOH++83etN/PxkN48/Dhx9NDB1KtPJ48Zx7p0Cu1Zp4ULn65MVFfyzJtlJQZ2ItF6vvMIsXEUFz5LXruVfw3PP5Vf//sCJJ7pXmHzrLeC77xI6RLdiH9amrrl2OpkzJ7pS/wBnzkajLnPVmDHOzcJDXXklG4C3acNedeutB9xzDzNgdTp1AqZMAb76igHen38yQDvnHPaMP+YYrn1pPLP2xhvDm4+XlbG4TElJdK8tknvvdT4RBNw7ZwCcXtk4qPN4OCV0t91aPq7meOABZhhDV5gsXuwesMfErQRpTk7T5UkToaaGH7rQD4e1/N5pmqhkve23d/5ZLiwEdt01+eOR5FBQJyKt1wMPcG6ek6oqZuTGjnVP0QSDwJ13Jm58YKVEpzVc+fn8w93a/fJLdIVQcnKAIUOi26fbehO/v+lqjh4PA6B//gHefJOz4CZNYmeKxkvYt9oK2H9/Pl/v3gyqvv+erRi23DJ8399/73yilpMTn+mFbj8KAANPN5tuyusj7dszmA0E2Gz9009jr0AaLzfc4Lx9+XJ272iR008PT8cawwWZ66/fwp27qKriIsptt+UH54IL+OEHgGXLnBeCWpvwi06SnrbcEhg6tOHHNC+P06mPOip145LEUlAnIq1XNOmN8nL+NXQTaV5aC9XWsghIaAVEYzht7+23U3fCnC7eeqvp9V4A37OiouiTFkccwfe4sWCQJ0pNefZZVpccNgx45hlWDj38cAboLalNtummzturq517+MXq+OPdb2tqqdiwYQyYPv8cmD6dVTY32qjlY2quSMtdo+k5GNFZZ7GsaCDAqytt2jD9+vrrLdyxC2tZnOnyy/nmzpjB9G+/fkyFGuM+/3jlyqYXk0pWev11Zvc324wXjc47jxeGol13K5lHQZ2ItF4jRkT3F27AAOftHg+w997xHVOIhx5i77TQ6YXGsBH1Lrsk7GkzxvXXR5el83iAkSPdp1U2tuee/GgUFPD9zslhlu7eezmdMpLHH2frh8ZtC0pLeZLVksTJJZeEX1/w+7mUqkOH5u+3zrnnsod2Y+3aRbd8NCeH/QTdgk8nVVVc4xNNm4dYbLyx+23RZmxd5ebyastnnwGjR3Ph659/8uw5ET7/nPNxG8+9DQa5qPSUU9wfay2vKDQ1b1iyTk4OE7o//8xrj6NHM5su2UtBnYi0XuefzwoKkVJefj/P8p3WygSDLEaQIA895HweN2UK8PffCXvajLFoUXT3q60FXngh+v0awwpxH37IQiRXXMGqk02V5reWa+rcWiKUlQHvvRf9OOr8+y9w003AQQeFZ/pGjAAeeYT/r6nhfd3WxTXFGAZYp57KtTc+HxuZz5oV3lYhHu67j0HyVluxbcIppzTMSrfEE084rzndZx9OQYuL7bZjJDx8ODN2iTJpkvvc2JoaFm6JNC+4tpaLN0UkqymoE5HWq00bVou79FLnwM7rZUosL8+5GofXy7P9BHE7j/N4om+onc0GDoz+vmvWxLZvY3jo77iDGcGmsk/Wsil4pGC7OSX+Z88GNtyQFS7Xrm04y87jYYIoJ4fVNTt0YMDSpQszhs2Rn8/Hrl3Lz9gbbzhn71rqzTcZLK9dy895RQXjjvPOi8/+Bw1igmujjfg++f2sbPrhh/HZf1J17ercbb5OU3N6Kys5DVNEspqCOhFp3fx+NhN+5ZXwM+5Bg7hwq1Mn52maPh+bkyXIoYc6L+fr0iX6qYSZYto0ZogOOohZFrdsV6hbbuG5bmhGxik74/UC++4bv7E6ef11tiCIxOvlVMlYHH88sGqV8zWFYJBJnBtuAG6/nQFSVRUDy1GjgNde4/3+/ZdZ3913Z2+6t99u2dq+eHCq5FlezvWIjbc31+DBbGBfW8t93n13hlaMPeKIli2gLShgilJEspqxqf7NHqXi4mI7ZcqUVA9DRLLVhx8Chx3WMAXm8wGHHMJqHOuvH15YpU0bpkratUvIkP7+m72EV6zgSWleHrM948ZlV1nqJ59kOf+qKgYqBQVcE/XNN86VP0NNn84CKFOnshjA8OEMGCorOSPN5+NUwrrbE2XAAGDmTPfb8/IYsMRSeW7VKk5LjNSDz+vl++WUidxgAz7+++8bBnEFBQwWH3oo+rHEW5cuLKzSmN8PzJ2bmOxgRps8mb+LlixpuN2YyBF6IMB1v2+/naERrYg0ZoyZaq0tDtuuoE5EBIySJk0K356fzyIDs2YxYqhLIfn9zOIlcE0dwDjyuedYk2HjjdkjPVFV01PhtdeAI48M3x4IsFn4OefEvs9581jU5JdfgJ12Yn/5Tp1aPlY3b7zBZIrbn9PjjmP3jKKi2Pa7di0TwW5BXU4OEzAffeS+pMrtnN/nYxHFTTaJbUzxcvDBrDXSeGzrrccG4a29sqsja/k76rnnOO17gw1Y9vTxx93nY2+5Ja986A0VyRoK6kREItlgA+dmX4EAr5L368cz5y++YEC3/fY6UWqhSZNYg8YtINl1V66LSme1tTyvdso6AVzntmwZA7Dm2HNPfuQaT7/MywN69QK+/JLn7bEWzgkEOB2xqeIviTJrFrDjjsxA1xV28fk4RbRzZ1bwP/TQ1PTyzihVVewn8dFHzrd7vbwqoCydSNZwC+q0pk5EBGBVDKcgrayMvaBuuompsn335Zn2eedxjl82qlus9eqrwIIFCXmKCRMiB3RAfMr0J9rixZHbHT72WPMDOoBJmZ49OdM3P5+Bz4YbcgnoL7+whsagQbHv1+tN6HJQV5Mnc+3keedxfd+uu3KqZZ8+jE/Gj+drPvlk3patP2Jxk5fHqeNurVlycxXQibQSCupERACWFywoYKm8xv7+G7j6ajb7qa7mFMyHH+Zcsauvjn+TrVRatIj9tvbfHzjtNGYoTz21+XXyHVRUcPlipIAuP5/TJtNdu3bORUwAVswcPrxl++/Zk9NJX3qJlTg/+YTfH3po/TWIzTeP/bw9J4fZsGR68EFeH3nySWDiRBaX+eILfrR+/53/1k0eKi3l9NCnn07uGNPe3Lm8sNSuHX//jBzJ30/HHx/eViE/HzjmmJQMU0SST0GdiAjALNyUKUwPRHOGbC1TNKNHM8sXqZpFKv32GxetderEYO3xxyMXVjj8cGbnSkoYrFZUMC30zDNxG9LEiU3f58IL49AkOoJVqxiztmnDqYhHHsmlk6GBRTSKili/ovH5dCDA6wTxkJMDHHgg1xfuvHP9x7O2Fvj1VxbTccoG1jVOD+XxAN26MVPqltxJhFWr2PKh8dKvYNC9L3ZZmdqrNfDxx7zIMn48sHo12xQ8/DAb/R12GBdIFhTUfw0YwDm2ItIqKKgTEamzySbACSdE7gnVWFUVMH8+8M47iRtXcy1axDP+N97g1fxff2XD9cMPZwpk1ixe+V+9mvdfvBj48cfw1FNpKSt9xEmkDJ3Hw+TDzTfH7enCBIPMGD33HGPX8nL2Tevdm9kvvx8YOhRYuDC6/T35JO/v8zHI8/uByy6LvX1BLN55h8HZ1lszIG18TSE/n+/hCScA7dszpj/6aAbUixYB22yTuLE5mTTJuT1HUwoL4z+WjBQMAv/5j/MPz9Kl7AXy++/8AJ9+OgPA776LvTqPiGQsBXUiIqF22sl9Pp2bkhJWrEg3d9zBgCx06mR5Oat2nnkmK2z068fKFCeeyIZmbsVfVq+OvHgsBnvs4Xxu6vFwrVUc40dHn37KOLyqqn5bbW39mCorWXeiTx8GZ25N4OsUFDDI+u03ZsCWLQOuuSZxS5l++IGz6lascC96mJvLGOCJJ4B//mEhl5deYiLaaYbx9OmcjtmtG7OBbnU3mqtNm9h743k8wEknxXccGeu33+ovvjipquLP55o1bJjYs6fW0om0MgrqRERCbbopUxoFBfXb8vOdz4TreL2MANLNl1+6Twuti2hqavj/114D7rrL/cr+ggWsXLLvvoxaWqCwkLM5/f767E1BAdsC3Hln885Ff/qJWakRI7juLFIAMXt2w4DOTTDIpt6dOkW3tqt7dyZGG/ewB9hcvV8/flR8Pi5TjJSxjOTuu5tuzl5SwvczGpMncwbxBx+wncDXX3PNntvUx2Aw9tnGgwfHlgCvc9ddqW+UnhYKC6N/I2pr2RRRRFoVBXUiIo098QQ7Mw8axHUp117LM92ePZ3vX1vLBr/pZtNNIwejocrLeRbvtgbHWp7JT5jAuYstLJwyYgQwZw5w3XXApZcyoHjppeiHG+qKK4D+/Tmd8o03eCj22sv9HHjTTcPXwEVSXs71bNOmxT42APj5ZwZ7c+bwbaus5JTNnXZq3v7qioo0Zdq06OLvyy7j+rXQ96usjP31Tj65vgDq2rVM6AYCDEy3355Zw2h4vVwKtt56DYP2nBzuz6l1QTDIhu5ffBHdc2S1bt34IYpGZSWjcxFpVRTUiYg05vEwVXHqqUz/HHggsMMOPLFyUlAQe6OwZLjkktiqYXg8wJIlkR9TU8O1d3E4015/fQZkt93GTE5zMnR//AHcemv49okTGSQ62WcfHspYeqBVVACPPBL7+AAucXIKMCdPZluCWO21V3SH1eNhcAbwsP7xh/M4pk51fnxtLQPlbbZhYHfggayZU1nJgGvyZE7nXLQounFvtRWXf40Zw+Bw+HDgxhs5rrPOcn5MZSXrFwmYTd9oo6avfBQWpudFJhFJKAV1IiKNPfIIS4afeipw0UU8qx00iPMFnU6oamtZPTPdbLMN68b36hVdlYr8fK7daWpun7XOjdpT4Lbb3G+75x7n7V4vZ6YefDADO4+n6YAyGGyY9aqq4hLEaGbERcpmvftu049v7Oyz+fFsKijt1Inj3m479rbbfHPWAvruu4b3697dfR+1tZzKOWoUg6vGfeMqK9mqIFo5Oazp8fTTzKpedhmzd/37N5zxXMfnY/AvYEO/uXNZdeaxx7g49MQTG75xgQCr5xx4YKpGKSIpoqBORCTUjBlMG4TOb6ut5Znwt9+Gz3vz+xkd9OiR3HFGa//9mQr5809g7Fj3uW4AK4I8/njT+7Q2+eUTXUSKPyOtWevUifFuRQUDtG++iRzcFBTwMFdUMPPWti0bf2+wAaeORhKpiXr//pEf66RjRxY2OfNMPv9WW3E8dYc1L4/jffppZtKmTWPwVV7OmH3IEBZOqXP11ZHXu9XWMvisy/qFqqriFMmWOuoojjs0uPZ4mHQ66KCW7z9rGMN5u6edxopDTz3F6eK7784LT6NHc1GpW8EjEclaCupEREJddpn7bXXVNeqydYWFrL//3HOJH1dLGAN06QIMGwb89BO+/899GNH9K2zr+wkX4Q4swbpppVVVTVcQ8fkYKWy1VeLHHQW3aXsAz3ub4vHw/HeHHTirdMYMniuHxr2BANfhHXMMezy/8EJ9MPjHH+wQEWmK4P/+57y9sBDYb7+mx+ika1dmIq+9lgnW7t0Zv48YwTWKP/3EGH3t2vDrEDU1DdsOHnsscNNNzgVe6rhlJH0+vnctVVTEBNTWWzO4y8vjfr/6qnmtEFoNYxgRT5zIKxMjR8a2YFREsoaxGVJWqri42E7RxHoRSbTNNmM/t0hyc3kWfMklyRlTHL3xBpcJlpfzRD0PlShECaZjG/RGE43ZiorYQfqyy9LqTPuAA4Bx4xpu22wzFiZpblX3Tz7htMJ//2UVyZNOYrX4Pn3Cs4PGcAnmm2+676+uVUPdn9z27Zn83WST8PuWlfG8vKlky8knc5lVXcsFn49LrqZO5eMfeYRN3J3aHowcGT5tsrqajdQnTAifZunEGE4D/flndsWIl7//5mtv357v1+LFDKwjZTxFRFoLY8xUa21Y5SRl6kREQu26a9P3qa7mnDW3RVtpqraWJ/OhlQ6rkI/VKMJ1uM79ge3asaLF119z7mEaBXQA8N57LOAxcCBb791/PzNVLWnTNWQI8PbbwGef8T3z+zmD1SkJYm3TBU/uuw9YtYpTNX/4gb3jGgd0H37IAqtt2vDrggvcE6dz57JYaWgPvYoKLnV87TV+v/32zu9BYSEL0zSWm8vHHnhgdMkev5+BbDwDOoBr7Nq3Bz7/nNNLN9qIieY99mhxNw0RkaylTJ2ISKj584EttnDv6hzK5+P8u3if1SbIggV8aU5ro3pgIRahd/gNW2zB7NyoUYwKq6q4fufll3nm3YqsXs1pj40zdTk5rFcRzXJEN2PHMksW+ic5J4cNxJ165D33HAumOPWDP+64+hnBBx3EzFvdMc/PZ02fadMix+azZjFIjjQb1+PhtNSWBtBOFixgX7/G73Xv3gxc1VdbRForZepERKKx4YacFzd4MOeAeb3uZ5A5OcDHHyd3fC3Qrh3jMied4NKSYcAAZudWreICrcpKRgnDhydqmGmrbVvg3HMbFhUxhhmryy9v2b6POy583VpNDfDii8DKleH379rV+WOZl8fAp86bb3KmcN++/GhffDGXXjWVbO3Xj683kmAQWLiQzdzjza3B+p9/MjMrIiINKagTEWlsyy3Zh62mpn6hkZO6M/oM0b49sO++4VPrClCKSzA6/AE+H1M6jdM1NTWsYJEmbQ2S6bbbgDvvZIDUti2Lk3z7LacINtfPPzNedlIXODW21158/sYdNnJy2ImjTm4uk6xz5rDy5Y03Ri6IUsfjAe69t+mPt9fLtYbx9uWX7re9/nr8n09EJNMpqBMRicQY4L//de72XFbGs+sM8txzXDbo9zMo8PmAC6/Mx9FP7cM6+EVFPOv3+4FHH+XiLSe1tcBffyV38GnAGLYS+O03Ji/fe49ZrZZYvdq9KEowyACyMa+X6/369+ehKizkLOAxY1jMJR6OPpoFaPbem0VKnMZoLbDttvF5vlCRetMVFsb/+dJSbS0j/qVL+X3jMqYiIiG0pk5EJBobbsiFPqHy84Hrr2cN+Qzzxx+sKti/f8g0u/JyTietrmalkGCQVSvcTibXrIku7SMRVVay91xo0ZM6gwczaRzJ/Pm8vrD55olrT1ZSwsIrf/zB5/J4+PF/9FFOHY23b75hO7bGcnLYc9up0EtGq6nh3NJvvuHPVFUV+3WUlfH/wWD9z2GnTuxHd8IJqR2ziKSE25o6BXUi0nqUlgLPP88Ux0Ybca1YpJRAnZUr2QjMqWrEhhsC8+ZlZ+WGmhouxHOKNrp2rc8gSIu9+CKnTYauI+vUiYnSpta2JUtZGfDss8xOdu/OQi1bb5245zvuOFY1rWsin5vLypxvvplFP25r1jB4e/VVZuY8Hi54dFpQGCo/H3joIfa1aKXmzwfuuAOYPJltMy++mGtHRbKdgjoRad3++QcoLgaWL2eQkpfHs8T33wd22y3yYz/9lJkrt9+Xfj+bmZ1yCs9y0zl7FQyGL8SK5MYbWWkj9CQzL4+17w8+OP7ja8WmT2cvu8WLGbyceGIrmmrowFoGkE89xcDuhBOAww6L7eOb9gYPZmGm6urYH9uKL6zMmAHsvDN/LdXUMEPt83GiwY47pnp0IomloE5EWreLL2YDs8bZtvx8njkOGeL8uLvvBi66yD2gC5WTw0Dx8su5Di+d0glvvslm6QsWcPHV1VcD55zT9BitBW65Bbj9dgbDnTrx///5T3LGneaWL2d/uVWrGONGk/hNhWCQhzqdPpKt3owZjECceoxEwxjO3c3Nje+4MsCeewITJ4Zv33prXhwRyWZqaSAirdsbbzhPn6ysBIYNA959N/y2Rx/lerloL37V1HBd2m23cd5Yunj/feD44+vXBC5fDlxxBQPWphgDXHklM52rVzONpIAOAHvP9+jBDNL557NAyY478m1KhGCQh6FuOmI0Zs7k1DSvl9ccdtkFWLEiMeOTGM2dy4PSXJ07t8qADgC+/tp5+48/xvbzIZJNFNSJSOtQUOB+W0UFcMEFDbcFg8xmNecMoayM2ax0ceWV4dmA0lLghhs4jfL66/lvU52mAwGletaZNo0J2cYfj2+/5UzceHv6aaBLF6BbN7amuPrqposhLlnC4iYzZvD7YJCdKDbYwHmZpCTZgAHNm3YJ1BdpaqWKipy3+/2JKxYkku4U1IlI6zByZMOu0Y399lvDztxr1rSsAdfy5c1/bLzNn++8fdUqrgO87jr+u+mmGdWmYNo0thAsLubs2kWL4rfvigrW1DnvPNajaPxReOopJnmdTJzIgCpexozhTNm//2bcXVLCJOs110R+3D33ONfbKC3lMklJsU02YeNIp2aA+fmcEr7RRpzTG3pRqmNH4MEHWeiplTr33PBf534/cNppuu4krZeCOhFpHc48Ezj0UPfbc3OBa6/l9EKAxU4ad+muY0zkaVMeD7DHHs0fa7xUVAAvvRS5cEtJCaeXlpTwtZ99dvLG1wJnngkMHAi88w4wdSpw111sz/DLLy3f9/LlbA8wciSXYV5yCbNbv/5af59I8X5OTnxj+muvDU+0lpWxOXikRE+kVghjx8ZnbNJCr7zCD1jnzqz00bs35/N+/z2rfsybB/z+e/3PaTDI6P6UU1I98pS64grgyCP5K7qu3+aBB3Lmu0hrpaBORFoHrxd44QXgf/9j9cbGqqvZ+2nzzRkpbL0118c5OeAAnnTttVd4cJeby7lBN9wQ95cQkz/+YLuFM86IvkJeTQ3P9tO8gNbbbwOPPdZwm7UMtC68sOX7v+wyZv1KSvh9WRnw778Nq8cffrh7XO/xAJtt1vJx1Pn9d+ft1dWRg8sBA9xv69WrRUOSeMnL4++kZcv4++aPP4BnnnE/eEpDAeDP3lNP8Wdj7FjGvq+95n4dTqQ1UPVLEWldrOV6txtvrD9rbyw3l1MxGy9a6tKF896OPrrh9q+/5iXi+fOB3XfnlffevRMy/KjtvTfnAYZOKY1GTg7n+KXxyeOgQawC7yQQaPl6sYIC54KEOTkMovx+fjT22QeYMKHhfXJzgTvv5PSweHjwQe7L6U/1eusxFnAr8f/XXyzk0vhj7PGwVWPWNfAWEWkF3KpftqDskohIBjKGqZhp03hp14nbnLacHF5Zt7Zh0LPTTszupYvKSp61NyegO/hgzJhp8MEHDG5GjGAsm07+/tv9tkjLJqNRWemeoA1t8efxAB99xKTKbbcxuNpoI14r2G+/lo2hzuzZvD7gFND5/ew0EalnW9eubLdw8MH1r8nr5eMU0ImIZBcFdSLS+nz2mXtAF8nixVzv8uOP6V15rjlZtjZtYDt0xHlFz+LJQYxrc3PZ0eGll1iQJF0MHQo8/LBzsHPeeS3b96xZjG2d4vqCgobTuzweTskMnZYZT88951yQ1OPhrNpTT216H3vvzczl1Klsh7DDDlyDJCIi2UVr6kSkdVm7livqI4mU/igt5dq7lSvjO654ystjd95oa3sHAsDTT2PiY3Px9GsFKC+vb7lXXs62dG4zVVPhqqtYALBx7Dp4MLs3tET79u5vW6Q1aomwbJlzsjU/H9hyy+j3YwwrhO6zT3QB3ZdfAscdBxx0ECuANrfqvoiIJI+COhFpXd55J3Imq3174MQTI/e1y89n6iOdPfEE598VFjJIjVStc+utgeHD8fzLOY7r0bxeFuJLF927M6N2ySWseLnzziz7/8UXsfeoKilh4HLvvUzAbrghsMUW4XF9IMBZu8nk1omiooKV8BPhttuYCX3xReDdd4GzzuL1AQV2IiLpTdMvRaR1WbPGfa1Zfj4wfTqLnOy1F3D++c4LuKqr2QU6nfXqxd57Y8awNFyvXmxX0Djl5vOxT93/swDCg950q6nVpQsDkJaUMP/uO2avgsH6oGWnnVgkdcQIBlU5OVxnd9llwLBh8Rl7tKZNc7+tQ4f4P9/y5fwohPa2Ky3lj8SbbwJHHRX/5xQRkfhQpk5EWpe993aOUHJzuc5u/fWZyTvmGFaZaFx5IyeHTbpjmf+WZNYykfjJpHys2e9Izlc8/nietR92GF+rMQz0XniB7wmAY4f+jQITXvaxptpin32S/SoSq7aW6wTXrGGcW1nJr4kTgb59GdCNGMG3Z/Hipht9J4Jbsjg3N3LitbG5cxmQFhYyeXvDDZxe29gXX3DfjZWWAm+9Ff3ziYhI8imoExFHa9YwC7LTTjz5/fTTVI8oTjbZhHPKQs+YCwrYe65xKmbgQDZDateODbx9Plaa+PDDpA45FvPns0fabruxl1rXrsADD6y70e9nyqWigpHMH38Aw4fztjVrsNfVO+I4+ywCKIUXNfChHH6U4fk9nkJhYcpeUkJMnRq59UFpKftCP/54YrJi0Tj9dB6yUPn5kXvkNbZkCbD99sD77/M1LVvGALVdO+CeexomrYuKnGcmezypew9ERCQ66lMnImHWrgW23ZYZirpS6IEAy7VfcEFqxxYX1gKffMKArbISOPZY4NBD3QukVFcDc+ZwvV0ad222lknE+fMb9iYLBIDx44FddnF54PTpvHFdc7bp2BofYD8UoBRH4DV0y/+XaZw//uDOhgzh3MXzzwdmzMBf7fri4a0ewbTALth2oMFZZzGYTGdff83WA5GadwMMqn78kdcCkq2qitnCjz9mBq2mhssfx42LvoLlFVewtWJlZfhtfj9bLj75JL+vrmZfuxUrwu/35Zf8nZDRfv4ZeOQR4M8/uSjxP/9peQ8MEZEkc+tTp6BORMKMHg1ce214vy6/nw2Ni4pSMy6JbOpU9j5vvGzOGOCII5h5CvPnn0zthS6kcuP3M7oIBhlhVFRgDvpiR3yDCuSjEn74fMwmffMNsPnm8XhViVFdzcDzn38i36+oCHj22dS2dPjlFwaWy5ez2XlZGa9DHH2083TJUHvuySmlbvLzueSyZ09+/8MPLJRSXs7PTXU1cNddwJlnxu3lpMbYsVwUWF3Nz25BAS/QfPedfqGJSEZxC+o0/VJEwrz7rnMD5txcQNdW0tc//zhXf7SWAYGju+5yTuM4KS+vX4S2LggciYewBkWoBOcJVlTwLuec04wXkES5ucDLLzc9jbG6mjFvKm22GWOPyy9n3ZuPPgJGjmSmsan+8v37Rw78jGEbiMmT+f3WWzNDP3Ys1xMuXZrhAV1lJfDgg1xLWterA+Bc1N9/B+6/P6XDExGJFwV1IhKma1fntTW1tewPJulphx2cm1UHAhEyTd9+26LSlpMwGLbRnxJrgc8/b/Yuk2bt2sgBj88H7Lhj6jOO8+cDDz3UcA1gaSkDvXHjIj921Ci2LXRTUcH2BbvuyqKvffuyo0eXLlximtGNyqurmbq++GLn6LeigsWRRESygIK6ZlixglPT9tgDOOMM4KefUj0ikfg677zwAg1eLwtDJrsBs0SvqAi49VYGcXVBud/P43bKKS4P6t8/9uZuIXxwnrbp8zV7l0lz773OGWmAgdBxxzFjlWoTJzov9ywpAd57L/JjN9qIy0f79nW/TzDI+GbhQk71fPllYLvt4tCKsbKSTQD/8x+mGX/7rYU7jNHbbwMzZ0aeWtymDYO/N99kBHz33c5tTERE0pyCuhgtXAj068eqgJ99xgXm223HP5oi2WKXXYA77mBw0LYt/918c+CDDyL37ZbUO+88Fuc8/HAmKW69lVPrXHupX3QRF1Y104l4Bj40jIx8PuCkk5q9y6RZvdp5e2Eh1wQ+9ljkHvSxevVVTm/s1o1rHOfOje5x7do5x925ucB66zX9+EGDWOdn/Hg2V29qHV4wyEzghRdGNz5HpaWsHnvaaUwF3nknrwg1lVqMpxdeiFzitKCA49tuO6Yn772X7T823BD4/vukDVNEJB5UKCVGJ57IvxONZ3Ksvz6wYIFOeCW7lJbyan3HjkzoSJb6/HMunJo3jymhgw5iJP/aa0xZlZZyTmUwyNt9Pva9++YblM2Yh4O97+ErszNy/TmorjbYZRfgnXfCs73p5tpreYGu8ZLCdu24BrGp4CcWt97K/nDrCozC42HwOH06Y4hIKioYCK5a1XC73w/MmAFsvHH047CWSamTT+b000h8PvdMZpMuvpiBXGMdOrCvQiyN9prjmWeAU091X3SYkwOcfTbT26NHh2fz8vLYnO+AAxI7ThGRGKn6ZZx07cq/R435fFz30K1b8sckIhIXpaXM2tWdcC9cyKijZ0+2M3jjDUYip5zC5mchZs9mxfjNN+dshkywahVQXMxiIGVlzIbl5zMeGDEiPs/xww/ApZeyLUFjXi9wwgn1LQUimTKF8UVdVcraWuDpp5s3zvnzeYyaqo/TvTuLpjRLQUF9BBsqN5eLAbfZppk7jsJ77wEHH9ywr0eoNm14YDbckL0q5s1zvp/PxyzjYYcxGv7yS74h223Hea0iIingFtQl+FJZ9mnb1jmoCwaRdc15RaSVaTzXsFev+r58227LXn4u+vfPvGxuu3Y8t3/6ac4K7N2byZt4rRu95hr2dnS7dlpbyzghGsXFbCT+zTdMKu28c/Myoc89x7XgTV3PDQQ4M7dZVq92T/FVVye2N9wbb3ANn1tAl58PfPVVfXo0Ujq2ooJvQufOnKazbFl9n4cjj2SfS7feliIiSabfRjE6//zwv0d5eSwt3aZNasYkIpKt6tojtG/PmXInnBChPUMzFBYC557L9aKPPhq/gG7aNE65bCp42mCD6Pfp9XK965AhzQvoli1jQFdR0bBKak4OsNtuTEwVFfHfM89k3ZBmcwt2vF5g001bsOMIrOWgI6Ug99sP2HLL+u9POy1ykPn773xzfvuNlWnWruUb+PrrwOOPx2vkIiItpqAuRmeeyaUk+fn1BSS2357TdUREJH6CQVYZfuIJTpVcuxZ46SW2boi2tV6qvPQSEzqRBALAFVckZzwAK3k6xVrWAjvtBCxaxAJgf/3F5XBNJaGsBR5+mNM0vV7203vvPfCP49ZbOz/opJMSt/h89erIEX9BAVOxoc45hx+ySGNyyvqVlbH/nYhImlBQFyOPh3/EFiwAXnmF6xwmTeI0HhERiZ+JE4Fff20YwNXUsOL8G2+kblzRqOtx7aZtWyZ6dtstOeOprGRLQqc+htbyq2NHLnWLtjfdPfcAl1zCNYnBII/VEUcAH53yKlsJhAZK+fkM9O6+Ox4vx1lhoft0SmO4uHHIkIbbc3MZiV5xReyVcUpKmjdOEZEEUFDXTN26Afvum/qmtCIi2WrGDOcgpKSE9VvS2RFHuE+R7N6d/U6POSY5Y1m5kusdX33VOdjMz+d4Y1FbC1x/fXjHgPJy4KqnN+aBC517mpvLqDKRi89zcoCRI53XSNxzDxc5urnxRqYnO3SI7rny8tg3REQkTSioExGRtNSnj3NFep8vcjPtdLDTTqyo37gFYK9ewNdfx7ddQlP++18WMnVq2eb3sx9drMUoV692Lm4JAL9ahx4LHg/ndibaLbewX4PPx+mWhYXsJXHuuZEfZwzvs2JF0+0WAgGgRw82VBcRSROqfikiImlp/nzn5UxVVbFnllLhvvtY2OXttxkEDR/OhvAtVV3Naf/V1cDgwU0Xk3zjDeeMp9cLTJgA7Lhj7GOoW1PutN9N4NJV3S0KjKecHOD++1mlZvlypkUbR9aReDxctPnVV86377EH+0gcf3x8O9OLiLSQMnUiIpKWXnjBuXpkfj7w55/JH09zDBzImX23384WZzffzJ51bhX3m/Lll+yXeuihDGw7d256faFb4snjaVgIMhZeLzOAjQPKQF4Nbsq/IfwBVVUNI9q1a4G//sKyvyw++cS9VVxMvvoKGDSI6ccttgA++YTTJGNRWwtstVX4dq+XFdE+/RQ46ywFdCKSdhTUiYhIGGuB559nk+qOHdn4eubM5I4hUjDS1Ay5dDJ3LqeSnnkml3UddhizY7EmrkpKgP33B/75h60e1qzhlMrjj2flfTcnnsjZiKG8XmDXXVu2xO2CC4DRo7nG3ONhH+9XXjUYumt5fdBjDL+sZTuB998HDjkEwY6dcE6Pt7F+t0ocfkg1BgxgDZM1a5o5mMmTgX32YWPzigq+IaNGMZqOxTnnhJezzskB3n2XaVcRkTSloE5ERMLcdhsTEnPmMIj44AOuE5szJ3ljOPVU56mFXbqwfH6mOOYYLtUqKWEiqKSERWBuuSW2/Ywd67y9tpYBuJv//hfYbjvGWT4fe6r27Ak8+2xsz9+YMaxLsmQJx/Drr8CwQ7z8sDz/PPv9eDwM6CorGXAddBDw/vt4uPpkPB08HpXwYXVpLsrLmYU87bRmDubqq8Oj5LIy4KabnOeIOlm5kp3oG+/HWpa7FhFJYwrqRESkgfJyThkMLaxhLc91r78+eeM45RRg770ZjOTlMavUvj3w1luJa3UWb3//zQCu8TTSigrgqadi29fq1c7VK6uqGI+48fuBzz8HPvoIuOMO4OWXOd2xR4/Ynj9qdWnAqVPDK90Eg0BNDe7BBShDwymMlZXAO+84F3SJqLqamTonwSB7LjSlshI4+mjnBoi1tewmLyKSxjJoAouIiCSD21S+YJDJlmTJyQHGjOH5+qRJXEt2yCFNFwbJFEuX8nUNHhzd/YcMcV5jWFgIHHhg5Mcaw0zrTjvFPs5mueAC59Kl66xCO9fbSktjWLI2bRowdCi70zuxlgsPI/n6a/YoWrvW+XaPBxgwIMoBiYikhjJ1IiLSQNeu7uu9om1MHU/bbcey+8cck3kB3XrrsWaHE2uBY491DtScbLIJcMYZDQOeggLWH9lrrxYPNb7GjIl48974GB6Epx27dgU6dYryOWpqGIz9/bf7m3jCCe4NA5cvB375hWvx3AI6gHNWr7giykGJiKSGgjoREWlg0SLOoHMSS3V4oRdfZLLHycqVsVV+vPtuVrs8/HBg2DDgyScZP2XKdFQAQF4ebsaVaIfVyEcFAMDrtQgEgMcfj+G1fPYZ57G68XqBjR165k2ezApAvXvz30gVa7xeYPx498hcRCRNKKgTEZEGVq92T264BSfirm9fxg5OgsHYAmVjmJx6/XUWTjnySPcAPKWGD3cuUdq/P3DXXeizSR5mddwdo7b4BDsXV+D44w2++45rKKO2dm3kCLC2lm9UaP+Iv/5iWnPOHK6fCwYjp0qHDgV22SWGQaWBaFO/IpJV9OdZREQaGDjQ+bzQ7+e5usRu5MjwqaMeDwO+3r1TM6aEGj2afRzatOH3BQUsWzpuHHD22cCvv6Lb3zNx68wD8eVkH556qhnJsF13bbqy5Q8/AA89VP/9E0+wsEo0/P7YS5Sm0nPPsaypx8OKQv/9rwI8kVZEQZ2IiDTg9wMPPMAgpC4zFwgAG2zANV0Su9NPZzETv5/vZZs27O/WVOPwjLXeesBPP7HE5zXXAI8+CixYEN8ItmNH9t4IiZbL4cOrOAIP4SzMRj9Oz7zrrvrH/Ppr5Cmbdbp35zTNTCmQ8swz/OFcvJjfr1rFErYbbcTUu4hkPWMz5CpOcXGxnTJlSqqHISLSakybBjz4IKs0DhvGmhOZVqgk3cyaBXz7LWOGffbJrCbqaWvyZOD++zHt+VnYC5+gFjmoRg4MgCPxCp4quhBm9Sre97HHWHWncd+EnBxG2UVFDI7OOiuzDk6vXlwM6yQvD7jzTjZWF5GMZ4yZaq0tDtuuoE5EREQyWbDWonf+X1hc263B9gKU4MmBD+PIKZdwQ1kZFzguWVI/DdPvZ78It+7u6c7aphe7BgLA22/zSoKIZDS3oE7TL0VERCSjTf/BYHVeeC+EUhTisZyR9RsCAWDKFODUU9k/oU8frj17883kDTbejOFriaSsDLj99uSMR0RSQkGdiIiIZLTqasCT6zxdsjKnUSfz9dZj8ZSlS7nO74orgNzcJIwygW67releEEuXJmcsIpISCupEREQkoxUXOy+BCwSA445L/niS7vjjgRtucL89L09TL0WynII6ERERyWg5OcBLLzGIq+v7V1gIbLcdcNJJqR1b0lx1FateHnNMw8xjbi7Qti1w2WUpG5qIJJ6COhEREWuBu+/m2qScHGDrrYHPPuNt1dUsFV9ZmcoRShOGDmXHgmuvBc4/H3jlFWDCBCapWo22bYEXX2Q/wKFD2ez93HOBGTOaXncnIhlN1S9FRESuuYZl38vK6rf5/cAppwDPPgvU1LDC4KhRwPXXN11tMIGsBZ5/Hrj5ZmDZMmCHHbikaqutUjYkERFJErU0EBERcVJezuIZoQFdHWMYRdUJBIArr+RUtxS55Rb2lQ4dbkEB8P33rNYvIiLZK+ktDYwx1xljFhtjflj3tX/IbVcYY+YZY34xxgxN1BhERESatGSJe+XAxhc+y8qAO+4I354k5eXATTeFx5/l5cB116VkSCIikgac6//Gz93W2jtCNxhj+gE4CkB/AN0BfGKM2dRaW5vgsYiIiITr1g0IBqO//+rVXGeXxMVay5cDn3/Op3aKP4NBYPLkpA1HRETSTCoWBRwM4BVrbaW1dgGAeQC2T8E4RERSYsIE4OijgYMPBl5+mcu1JA5mzACeeAIYPx6ojeE6YSAAnHde9L3K1l8/qQHdrbfyKU85BbjwQouSEucs4UYbJW1IIiKSZhId1J1jjJlhjHnKGNN+3bYeABaG3GfRum1hjDGnG2OmGGOmrFixIsFDFRFJvKuuYjD3yivA2LHAaacBBx4YW6JIGqmpAQ49FNhxR5Y9HDEC2HBD4M8/o9/HzTczuGuK388qmUny5ZdsP1ZRAaxdC6xdawAYAA0/MP68Wvz3v0kbVuyWLgXOOgvo0wfYdlvghRdSNoVVRCQbtSioM8Z8YoyZ5fB1MICHAWwEYGsASwHcGev+rbWPWWuLrbXFnTp1aslQRURS7o8/gLvuAkpL67eVlgJffQV88EHqxpXx7rsP+OgjLjQrK2P08+efwKabRv/GLl3KuY1uioqAnXYC3n0XOOSQuAw7Go8+yvVyjeWiGl7UALAwCKKmqhbXXgv8+2/Shha9v/9mi4gnnuAPwfTpwJlnApdfnuqRiUgasBb48Ufg44/T9HdYhmhRUGetHWKt3cLh6x1r7TJrba21NgjgcdRPsVwMoFfIbnqu2yYiktU+/RTwesO3l5QwayfN9NhjzpUrKyuB4cOBr792f2xJCXDhhcCWW7rfJzeXZxpffQXstVfLxxuD1audE1o5qIEX1QAMLDyoRh6++YbTetPO6NEM7ELnGZeWAvfeC6xYweZy8+YpcyfSCi1eDAwYAOy8MydZdO/OiRMSu0RWv+wW8u2hAGat+/9YAEcZY/KNMRsA2ATA94kah4hIuigqcm5vlpMDdOiQ/PFkjYoK99vKy9lXzkkwCOy+O/DQQ5EvD6+/fsr60o0YwXYFjVXAhyr4G2yrqmK/9OXLkzO2qFgLPPig8/xir5dnc9tswyZ7m20GzJyZ/DGKSMocdBAwZw6v86xezV/nN98MjBuX6pFlnkT+lbrdGDPTGDMDwB4ALgAAa+1sAK8B+AnAhwDOVuVLEWkN9t/fOTbIzQVOPDHpw8keRxwRucjJL7/U/99aFlI56ihgt92A2bOZ0XNjDHDYYe63//MP8M03bIuQAEcdxSVodYGd19QigDJ0xErH++fmAiudb0qNd95pON84VFkZ8Ndf9dNm587lMXHKuopI1pk7lwFd47pWdYl8iU3Cgjpr7XHW2i2ttQOstQdZa5eG3HaTtXYja+1m1lqtJBGRVsHvBz78EOjYkVm7oiLW5njsMSYppJmuvJLZNCfGMBNUZ9QoTsl89VVWIYmU5TMGaNOGxVcas5bTNnv0APbbj6Unhw93XgDXArm5rJb65JPAkUcCp53hxZfXf4oRRR8jB1Vh98/JATbeOK5DaJk7Y1xOX10NvPVWYsYiImnl33/dr8epPmLsEt2nTkREQgwaxJockyYxnth1V6CwMNWjynDt2nHa3pFHAu+/3/Cyr98PXHst/z9nDvD449EFXh4Pp2befz8XeTT24IOsYlJRUR8YjhvHAPCxx1r6ihrIzeVLO/LIui0H4upTgDe25nSlqirGn34/8MAD0XdmSIr582O7f2Ulf0BEJOsNGOC8lNbnS2o9qqyRmkUCIiKtWG4usOeenI6pgC5OfD5gzBjO2enVi9/vtBOr02y1Fe/z8cdNF+MwBlhvPUZLEyYA/fo53++uu8KnCVZUAM8/zygrwbp3Zxw7ahSnZx5yCF/esccm/Kljs+GG7rc5tZDIy+NxE5Gs5/PxulkgwF+9AC9OdevG1qESG2XqREQkOxgDnH02v5wUFTmXHzWGX14vsN12wDPPNB1tuy1cq61lsJeE5uRdugC33Zbwp2mZK68Mn5ZqDLDPPmw9MX16/W2BALDLLgrqRFqRE04A+vZlZ5rFi3mx88wz+etaYmNshpQQLi4utlOmTEn1MEREJFOtXs01cI0Ld/j9DC569Ig+dXrggZzq2VinTsCyZfWXnVsTa4Hvv2fxmb592QzeGE5TvfRSVsCsrma5u6efZhD9wAMMor1e4JRT2KA8reaPioikF2PMVGttcdh2BXUiItJqTJwIHHpo/TTM2lrg2WeZTYrFnDlcEBLaew1gQHL++dzfDju0nuCupAQYOpQdhOv07csprG3bckrq/PlA587q3yEi0gIK6kRERAAW4/j8cwZku+/uvLYrkmAQeO014D//Ca/FDbDIit/Pqpvjx8e+/0w0ciTw1FMN20Pk5bEnw7PPpm5cIiJZRkGdiIhIS9XUAMOGMShsqoqmzweccw4wenRyxpYq06YB22/vHODm5/N9ai0ZSxGRBHML6lT9UkREJFoPP8wphdG0RaioaF6W6scfub5sr72AW29lM6d09frrQHGxc0AHcA2diIgknKpfioiIRGPuXDYcb7yOLpJY2xuMGcO+BJWVDJS++YbFRKZPZxGWdFJeDhxzjHubCGM4vVVZOhGRhFNQJyIiEo3zz48toMvJAQ4+mNU2n3iCAVvnzsBppzEQWrKEFTe33571u2trgVNPbdj/rrwcWL6cvQvuuCPuL6lFxoyJ/H60awc88kiyRiMi0qopqBMREYnGp5+639a+Pf+trGRQVlDAKo/XXsvpiX/+WR+svfYas1fW8t/cXOD661nq32laZ3U18Oab6RfULVnifpvHwwqhXbokbzwiIq2YgjoREZFo+P0NqzuGGjcO2Gwz4LnnGMxsvz0rPz72GPDHH+HBWt2URWs5RfN//wO6d3dfq7dqVdxeRtzssAMLoTi9JwcfrIBORCSJFNSJiLRm33wD3HUXsHgxsN9+rNZYl3WShk4+GXjoIRZAqZObCxx9NDBoEL8///yGjxkzJrqiKuXlbMLttj5t9ermjDixdt4ZGDwY+OyzhtMwO3cGXn45ZcMSEWmNVP1SRKS1euYZVlh84w0Gd9ddB2y6KfD336keWXq66SZgt92YsSsqYv+5HXcEHnzQ/TGxFDdZvpzTFp1YC/TuDbz1VmxjTiRjgPffB26+mVnKPn2Aa64BFixgBk9ERJJGfepERFqjykpgvfWAkpLw23bcEfj66+SPKVP89BMwezYDmQEDIt/3iy+YAQ0tfuIkNxe45BJO31y0yP1+gQCzYAcdFPu4RUQk46lPnYiI1Js927232LffRg4sWrt+/YARI5oO6ABg112BW26pz+55veH38Xq5/uzCC4H//CdyC4CyMuDEE4FZs5o9fBERyT4K6kREWqMOHdx7qHk8wMSJyR1Puvr3X+D225kZ2203Bl+FhcABBwC//BLdPs47D/jrL1aw/OYb4KWXmA3t3p3ZvmuuAWbMADp2BEaN4v6bGtPAgcBTT7X45YmISHbQ9EsRkdaqWzcGG435/Sy7f+CByR9TOlm0iMHTqlXhAbAxzLzNmgX07Bnf5501i73svv028v18Ph6/tm3j+/wiIpK2NP1SREQaquuX1lggAOyzT3T7sBZ4/XVgzz1ZAfLee6Or9pgJLruMxUucMprW8nXec0/8n3eLLZjRe+ABrrWL5PPP4//8khBlZUzSjh4NTJrkXuhURKQ51NJARKS1GjwYeP55ZoWM4bTLQIBTDXfdFejVC7joovpy/U7OPpvFPUpL+f2MGcCLLwJffdV0QJLuxo6NfHtVFVsWbLEF+7LFuxXE2WcDb78NTJjgfLu1PF6S9n76iT9SlZXsiJGfzx+rceOAvLxUj05EsoGmX4qItHZlZQzCKioY4K1axbNPYzgV89FHWcCjsd9+A/r3D28+XVgIPPkkcMQRSRl+whQW1gerbnJyOA2ythZ45ZX4VqV8910WZHFreN6uHTOJmR48twL9+7Mnfegpl9fLZPBNN6VuXCKSeTT9UkREnAUCwN57A59+CvzzT30QYS0DvnPPBaqrGz7GWuCss5wDjpIS4MMPEz/uRCsO+5sZrqaGr7e8nE3I49Qk/J8lFfj5qOtQWely4TU/Hxg/XgFdBvjjD7bua3wNvbYWuPVWFTIVkfhQUCciIvTBB+HBG8Czz8aVHj/4gD3YnOTmsghLpnvwQfdm4E68XuC991r0lGVlwFFHAd375GH7ss/QCStwP85ueKeNNmI2dfvtW/RckhzBYOTbRo1K2lBEJIspqBMREVpvPeft1dVAmzYsiPLww8C0acBjj7lPC/R4gFNPTdw4k6V/f64XjDYbZq1zUByDU08F3nkHqKz2YC3aYC2KcDluw1gMq79Tv36c8ikAgM8+A/bfn4frrLOAH39MryIkffqwe4Wbr75K2lBEJIupUIqIiNDFFwM//NBwHVluLtCjB7DhhvUph5wcBnlurr4a2GCDhA41aY49ltNTjzmGaw4jqakB9tuv2U+1ahXw1lvhsXIZCnAzrsBBeBcoKMiOgDlOnn0WGDmSGU6ABUkeeYSJ4kcfBYYNi/z4ZDCGyy2328759qKi5I5HRLKTMnUiIkKHHAJcfjmzQG3bskjKhhtyQVDoHLKaGjbAdlJQwIqZ2WSXXdyzkgCDXL8fuPNONidvppUruSsni9GLz3HccS2PVFatYuPyO+9kWitDVVdz6mJdQBdq6VJOY/3++6QPy1FxMWPxxknfQAA455zUjElEsosydSIiUu/qq1kY5ccfga5dgcMOi7woKFRODvDMMww+ssnrr7MwSeNMXW4uM3MDBjCj17dvi56md2/nmZ5eTxC7blMKPD8V2Hzz6HYWDLIp2iOPcNxDhrB2/o8/soiNx8P7XHMNC7w8/rhzz8I0Nn8+ry+4KS9nIZK33kremCK5/34G7h98wI9TZSWLm15xRapHJiLZQEGdiKS9NWuAuXPZNq1z51SPphVo25ZNtQBg0aLoH7fZZsDQocDMmTxY7dolZHhJt2CB89RLY4A99ohbpYvcXDamPv/8+uyT1wsUFHjwv1c2AzaOYWennsrm8nVTaadOdb5fVRXnBg4bxl57GaRjx8hLGK0Ffv01eeNpis/HAPPPP9kNpG/f7KgnJCLpQdMvRSRtWQtcdRVntO25JzMZRx3V9NImiaOBA6O/799/M+reeWdm+c44I3IqJVMMGsSedY3l5rovlGqmU0/lif+uu7LAxjHHsC7NxrEEdD//zECtqR57dUpL2Vcww6y3Hq8huDXvzskBdtopuWOKRu/evBaggE5E4klBnYikrccfB+69l0HcmjWcrvTOO8xkSAwqKthLrTluuSW6Sou5uVxnV1EBrF3Lg/X885zOmekOOogRVn5+/Ta/nwulEhA1DB0KfP45E4TPPccOBjGZNCn2qZTRTrFNM88/D+y1FzOaoYzhIbr88tSMS0Qk2RTUiUjaGj06PNlQUcET3Uh1K2Sd5cs5ra6oCGjfnkHIzJn1t9fWNr2P7bdnhLHLLjxL7tABOOII7rOwkOmQggKu0aqqavjY8nLgrruAm2/mnLNMlZvLuvOjRnFa6QYbAFdeyebf6bgOrXPn8Cgnkpwc4PjjEzeeBCoqAsaNY4Pv//6XGc0OHTiT9PvvWedHRKQ1gpAwCwAAHkVJREFUMDadmrlEUFxcbKdMmZLqYYhIErVvz0J9jeXlsbpdhw5JH1LmCAaBLbbgYsTQKZB+P6cMzpjBN3e99Xg2fO65sQUoJSXAm28Cf/3FgG/IEPd5sTk5DPoOOQRYsQJYvJiPyabWB+mkqgro2ZPTYaP5G+/x8HOiCEhEJO0ZY6Zaa4sbb1ehFBFJWzvvzKvwjc9Lu3ZlwCcRfPEFsHBh+Jq28nLeVufvv1l+r6qKfeqiVVgInHBC/ffFxcCXXzrft24Mr71Wv+233xgUTpkS44IxaVJeHjtyH3QQg+7a2sgLUQMBYPJkBXUiIhlM0y9FJG3dfjtjh7qZZMbw/POhh9Jz1lta+e236LI0AEst3nRTy9ZV3XVX/TTMaNTWcu3dNdc0/zklXFUV8PLLwG23AQccwBYTH3zAwL1jR/fHqWqHiEhGU6ZORNJWv37A9OlckvXtt8Amm3Ap0/bbp3pkGWDrraMP6gAuXly7lu0MmmO77XiQbrgBeP/96CovBoNcryfxMX8+fzhWrqzf9sAD9dNfnbJ1Xi/Ly+6yS/LGKZIES5fyV9rGG0d/rUkkk+ljLiJpbaONWG199mxgzBgFdFEbOJCl+EMrNkZSVAS0adOy59xiC+DVV4E33mDWLhpdu7bsOaXe0Uc3DOgABs5VVc4BXX4+sO22wMSJOuuVrLF0KTB4MJfrbrst0L07k9Ui2U6/xUVEWqCyErjkEvbZzstjefWffkr1qNZ5/33g9NObvl8gAFx/fdMn9tYCH34IjBjBqpqvvOJcQXPoUOCkk5reXyCgmvPx8vffTGvHolMnlpLt1SsxYxJJMmuBvffmpIHKSk4YWLYMOPxwtm8UyWYK6kREWuDwwznDbfVqoLqaSY8dd2SBx5Tz+YD77mPFGbcS9z168AWMHNn0/i66iC/4jTeA995jp+yDDgpfi2cMcP/9fF43+flcTzdiRPSvR9xF056iscWLWbW0OY8VSUOTJwO//x5eH6qqCnjwwZQMSSRpFNSJiDSDtcB55zG2CZ3ZZi2/f+CB1I0tzOuvA337supMQQHXWA0bxih00SJm1Zoybx7w8MMN18qVlrKS5scfOz/mpJOcp2Hm5fHM67LLmvVyxEGXLsCmm8b2GGuBNWu0rlGyxpIlztevamq45FQkmymoExFphvvuAx57zPm2qipW6k8b3bqx6finnwIvvsiAauxYBnfRmjDBueRoSQn7Tjg59lhgwID6wM7jYZ+8++7TWrpEeOml8CDa4+Hc4EhTYRuvwxPJUMXFnHbZWCDAaZki2UzVL0VEmuG225xPHgAmorbdNrnjaZIxrFDZXG3bulfTXLbMeXtdv7TXXwfefpsl9U8/nUVcJP4GDGDm9dFHWRmisJDZ0oMPBu68E7j22vAPbVWVKl9K1ujZEzjlFHbyKCvjtrw8YL31gJNPTunQRBLO2FhKXqdQcXGxnZJWl75FpDXLzQ1ft1GnTRtW68yq+hOlpQwSnPTowWBC0ldlJRd7/vJL/dluQQEwahRw440pHZpIPFnL+j/33ce1zoccwnpM662X6pGJxIcxZqq1trjxdmXqRESaYYstgB9+CN/u8wGTJmVZQAcAK1a437Z4MYulqCx++srPB776iv1BXnmFUzJHjgT23z/VIxOJK2OAE07gl0hrokydiEgzfPYZcMAB9UkPgMvF3noL2HfflA0rfoJBTpt86ilmdxYtcq+SmJPDoisiIiKSUMrUiYjE0e67s3bItdeyBsnmmwP/+18WLU869ljg3XcbVrt0s9VWiR+PJM5ff3HOWrduqR6JiIg0k4I6EZFmGjQIGD8+1aNIgMmTow/ocnOBRx5J/Jgk/qZOZaP4uuqXRUVMNe+1V2rHJSIiMdMCCBERaeiTT9xLe4Zq1w544QXWEZfMUlbGqxKh7QzWrGHd96VLUzcuERFpFgV1IiLSUIcOrAMeSe/ewPLlwBFHJGdMEl+33eZcvtVaNYUXEclACupERKShI45wbjQOcHsgwCqKubnJHZfEz4wZ7rfNnp28cYiISFwoqBORlKioAG6/HejfH9hyS+Duu9kHWdJA+/bAe+8xY9emDfuZ5eUxO3fIIcAXXwBDhqR6lNISkSr6tKRJvYiIpIRaGohI0gWDLJj400/8P8B2ADvvDHz0kXuSSJKsuhr47jtOyRs0SJm5bFJby4C9vLzhdq8XWLYM6NgxNeMSEZGI3FoaKFMnIkl36aXArFn1AR3Ac8uvvgK+/DJ145JGcnOZ0Rk8WAFdtvF6gblzmSqv06cPK2IqoBMRyThqaSAiSVVdDTzwgPNtFRXAN98whhCRBOvRo/7qSjDIJvIiIpKR9BtcRJJq7tzIt3fvnpxxiMg6Hg+/REQkY+m3uIgkVaSZXR4PcNhhyRuLiIiISDZQUCciSdWlC7D77uFLtIwB7ryT1fJFREREJHoK6kQk6V5+mfU3fD6gsJD/3nwzcP75qR6ZiIiISObRmjoRSbr27YFPPwV+/x346y8W4GvTJtWjEhEREclMCupEJGX69OGXiIiIiDSfpl+KiIiIiIhkMAV1IiIiIiIiGUxBnYiIiIiISAZTUCciIiIiIpLBVChFRERap6oq4MMPgZUrgV13BTbaKNUjEhERaRZl6kREJLtYCzz7LDBwILDxxsBFFwF//93wPjNnAt26AcOHAyefzPttvTVQWpqSIYuIJJq1wFNPAVtuCfToAZxyCrBoUapHJfFirLWpHkNUiouL7ZQpU1I9DBERSXfnngs8/XR9gJaXB3TuDMyaBbRtyzOb9dcHFi4Mf+zmmwOzZwPGJHfMIiIJdtFFwKOP1v9qzMkB2rXjr7zOnVM6NImBMWaqtba48XZl6kREJHssXgw88UTDjFtVFS9Hb7MNMGcO8MMPwLJlzo//5Rdg8uSkDFVEJFlWrAAefLDhr8aaGmDtWuC++1I3LokfBXUiIpI9pk5lZs7JggXAjjsCS5YAwaD7PmbOTMzYRERSZMYMwOcL315ZCXz2WdKHIwmgQikiIpI9uncHamvdb1+9GjjwQPfbc3OBTTaJ/7hERFKoVy9OWmjM41GNqGyhTJ2IiGSPgQOBDTbgmUqsjGHBlMGD4z8uEZEU2nRToLg4fCKDzwdceGFqxiTxpaBORESyhzHAxx8DW20V2+O8XuDQQ4HPP1eRFBHJSmPHAvvuC+TnA34/Jza89lrsvy4lPWn6pYiIZJeuXYFp07h+7ttvm77/0KHAe++xFJyISJZq1w545x1g1SpgzRqgZ8/mTWqQ9KRDKSIi2WnCBJ7FROLzATvtpIBORFqNdu2A3r0V0GUbHU4REclOgQDwwgucZ+TE4+F9zjorueMSERGJMwV1IiKSvQ44gFMrd94Z6NiRJeDatQMKCoBhw4Dvvwc6dUr1KEVERFpE801ERCS77bknv+rMnQusXMnqAG5ZPBERkQyiTJ2IiLQOS5cC223HYG7oUGboHnss1aMSSUuzZwOffsrWjiKS/hTUiYhI63DAAcAPPwDl5Sz9VloKXHABMGlSqkcmkjaWLAG22QbYfnvgsMNYTPbWW1M9KhFpioI6ERHJfj/9xNRDTU3D7WVlDPb69eOZa3l5asYnkiYOPhiYOZM/GqtXAxUVwI03AuPGpXpkIhKJgjoREcl+t9wCVFU537Z2LTBnDnD99cAeewC1tckdm0ia+O03Xvto/CNQWgrcc09KhiQiUVKhFBERyU4zZ7L5eMeOwOuvN33/8nKe0X74IbN3Iq3MP/8AubnOCesVK5I/HhGJnoI6ERHJLjU1wJFHMjgDAGPcs3SNlZQAX36poE5apS23BILB8O35+ewAIiLpS9MvRUQkuzz0EAO6sjJ+lZYC1kb32ECAvexEWiGfD7jvPv4YGFO/rWtXYNSolA5NRJqgTJ2IiGSXRx9lMNccXi9w9NHxHY9IBjnpJKBvX66hW7wY2H9/YORIoF27VI9MRCJRUCciItmloiL2x3i9QO/ewKuvAu3bx39MIhlkxx35JSKZQ0GdiIhkh6oqZun+/Te2xxkDfPABMGRI/ZwzERGRDKKgTkREMp+1wL77At99F/vUS2uBGTOAvfdOzNhEREQSTIVSREQk802cCEye3Py1dFdfDSxcGN8xiYiIJImCOhERyXyTJrHKZXMZA7z7bvzGIyIikkQK6kREJPN17Qr4/U3fz+sFPA5/+oxh12UREZEMpKBOREQy35FHAjlNLBP3+4GjjmIn5caCQeCQQxIyNBERkURTUCciIpmvXTvg44/ZOLyggF+FhUBeHtC2LTsoH3AA8MQTwC238PtAgPfz+YCnnwY6dUr1qxAREWkWY61N9RiiUlxcbKdMmZLqYYiISDqzFpgzh9Mp+/YF/v4b+OUXYIMNgB496u+3eDHw3nvM7h18MLDeeqkbs4iISJSMMVOttcVh2xXUiYiIiIiIpD+3oE7TL0VERERERDKYgjoREREREZEMpqBOREREREQkgymoExERERERyWAK6kRERERERDKYgjoREREREZEMpqBOREREREQkgymoExERERERyWAK6kRERERERDKYgjoREREREZEMpqBOREREREQkgymoExERERERyWAK6kRERERERDKYgjoREREREZEMpqBOREREREQkgymoExERERERyWAK6kRERERERDKYgjoREREREZEMpqBOREREREQkgymoExERERERyWAK6kRERERERDJYi4I6Y8wIY8xsY0zQGFPc6LYrjDHzjDG/GGOGhmzfd922ecaYy1vy/CIiIiIiIq1dSzN1swAcBuCL0I3GmH4AjgLQH8C+AB4yxniNMV4ADwLYD0A/AEevu6+IiIiIiIg0Q05LHmytnQMAxpjGNx0M4BVrbSWABcaYeQC2X3fbPGvt/HWPe2XdfX9qyThERERERERaq0StqesBYGHI94vWbXPb7sgYc7oxZooxZsqKFSsSMlAREREREZFM1mSmzhjzCYCuDjddZa19J/5DqmetfQzAYwBQXFxsE/lcIiIiIiIimajJoM5aO6QZ+10MoFfI9z3XbUOE7SIiIiIiIhKjRE2/HAvgKGNMvjFmAwCbAPgewGQAmxhjNjDG5IHFVMYmaAwiIiIiIiJZr0WFUowxhwK4H0AnAO8bY36w1g611s42xrwGFkCpAXC2tbZ23WPOATAegBfAU9ba2S16BSIiIiIiIq2YsTYzlqoVFxfbKVOmpHoYIiIiIiIiKWGMmWqtLW68PVHTL0VERERERCQJFNSJSMb7/HNgzz2Bnj2BAw8Epk1L9YhEREREkqdFa+pERFLtnXeAY44Bysr4/ZIlwMSJwIQJwKBBqR2biIiISDIoUyciGctaYNSo+oCubltZGXDxxSkbloiIiEhSKagTkYxVUQEsXOh82/TpyR2LiIiISKooqBORjJWfD/j9zrd17pzcsYiIiIikioI6EclYHg9w3nlAINBweyAAXHFFasYkIiIikmwqlCIiGe3664HSUuCxxwCvl9suvxw47bTUjktEREQkWdR8XESyQmkp8NdfQI8egM+X6tGIiEg6WLGCF/2mTwe22w449VSgY8dUj0qk+dyajyuoExEREZGsM2cOsNNOLKpVUcE12H4/8N13wMYbp3p0Is3jFtRpTZ2IiIiIZJ2zzgJWr2ZABwDl5cCqVcD556d0WCIJoaBORERERLJKMAhMmsTepY23f/JJasYkkkgK6kREREQkqxgD5OU535afn9yxiCSDgjoRERERySrGAMccEx7A+XzAiSemZEgiCaWgTkRERESyzj33AMXFQEEB0KYNe5juuCNw662pHplI/KlPnYiIiIhknTZtgC+/BKZNA37+GejfH9hqq1SPSiQxFNSJiIiISNbadlt+iWQzTb8UERERERHJYArqRERERNLIjBnAXnuxUXbXrsBNNwG1takelYikM02/FBEREUkT8+cDO+8MlJTw+4oK4OabgQULgCeeSO3YRCR9KVMnIiIikiZGj2YgF6qsDHjxRWDZstSMSUTSn4I6ERERkTQxeTJQUxO+PT8f+PXX5I9HRDKDgjoRERGRNDFgAOD1hm+vrAQ23DD54xGRzKCgTkRERCRNXHIJ4PM13Ob3A8OGAT16pGZMIpL+FNSJiIiIpInNNwfGjwe23BIwhgHdaacBzz+f6pGJSDpT9UsRERGRNLLzzmxrUF0N5OQwuBMRiURBnYiIiEgays1N9QhEJFNo+qWIiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIiIiIhlMQZ2IiIiIiEgGU1AnIiIiIiKSwRTUiYiIiIiIZDAFdSIiIq3ApEnATjsBRUVA//7AG2+kekQiIhIvOakegIiIiCTWpEnA0KFAeTm//+kn4IQTgNWrgVNOSe3YRESk5ZSpExERyXKXX14f0NUpK+P2YDA1YxIRkfhRUCciIpLlZs1y3r5mDbN1IiKS2RTUiYiIZLnevZ235+cDbdokdywiIhJ/CupERESy3P/+BwQCDbcFAsBFFwE5Wl0vIpLxFNSJiIhkucMOAx58EOjcGcjNZXbu0kuB//431SMTEZF40PU5ERGRVuDEE4HjjwfWrgUKCwGvN9UjEhGReFFQJyIi0kp4PEDbtqkehYiIxJumX4qIiIiIiGQwBXUiIiIiIiIZTEGdiIiIiIs//gBGjgS22QY48khg2rRUj0hEJJzW1ImIiIg4+PVXYLvtgPJyoLoa+PFH4L33gDfeAPbbL9WjExGpp0ydiIiIiIPLL2e10Opqfm8tUFYGnHUW/y8iki4U1ImIiIg4+Owz5+Bt6VJg5cqkD0dExJWCOhEREREHHTs6bzeGvf5ERNKFgjoRERERBxddBAQCDbf5fMDRR/NfEZF0oaBORERExMEZZ7Dypc8HFBXx36FDgQcfTPXIREQaalFQZ4wZYYyZbYwJGmOKQ7b3McaUG2N+WPf1SMhtA40xM40x84wx9xljTEvGICIiIpIIxgCjRwNLlgDjxwPz5gFjxoRn70REUq2lLQ1mATgMwKMOt/1mrd3aYfvDAE4D8B2AcQD2BfBBC8chIiIikhDt2wODBqV6FCIi7lqUqbPWzrHW/hLt/Y0x3QAUWWu/tdZaAM8BOKQlYxAREREREWnNErmmbgNjzHRjzOfGmMHrtvUAsCjkPovWbXNkjDndGDPFGDNlxYoVCRyqiIiIiIhIZmpy+qUx5hMAXR1uuspa+47Lw5YC6G2tXWmMGQhgjDGmf6yDs9Y+BuAxACguLlabTxERERERkUaaDOqstUNi3am1thJA5br/TzXG/AZgUwCLAfQMuWvPddtERERERESkGRIy/dIY08kY4133/w0BbAJgvrV2KYA1xphB66peHg/ALdsnIiIiIiIiTWhpS4NDjTGLAOwI4H1jzPh1N+0KYIYx5gcAbwA401r7z7rbRgJ4AsA8AL9BlS9FRERERESazbAIZforLi62U6ZMSfUwREREREREUsIYM9VaW9x4eyKrX4qIiIiIiEiCKagTERERERHJYArqREREREREMpiCOhERERERkQymoE5ERERERCSDKagTERERERHJYArqREREREREMpiCOhERERERkQymoE5ERERERCSDKagTERERERHJYArqREREREREMpiCOhERERERkQymoE5ERERERCSDKagTERERERHJYArqREREREREMpiCOhERERERkQymoE5ERERERCSDKagTERERERHJYArqREREREREMpiCOhERERERkQymoE5ERERERCSDKagTERERERHJYArqREREREREMpiCOhERERERkQymoE5ERERERCSDGWttqscQFWPMCgB/pHocLbQegL9TPQhJGB3f7Kbjm910fLObjm/20zHObjq+9da31nZqvDFjgrpsYIyZYq0tTvU4JDF0fLObjm920/HNbjq+2U/HOLvp+DZN0y9FREREREQymII6ERERERGRDKagLrkeS/UAJKF0fLObjm920/HNbjq+2U/HOLvp+DZBa+pEREREREQymDJ1IiIiIiIiGUxBnYiIiIiISAZTUJcAxpgRxpjZxpigMaY4ZHsfY0y5MeaHdV+PhNw20Bgz0xgzzxhznzHGpGb00hS347vutivWHcNfjDFDQ7bvu27bPGPM5ckftTSXMeY6Y8zikJ/b/UNuczzekln085l9jDG/r/ub+oMxZsq6bR2MMR8bY+au+7d9qscp0THGPGWMWW6MmRWyzfF4Grpv3c/zDGPMtqkbuUTD5fjqb2+MFNQlxiwAhwH4wuG236y1W6/7OjNk+8MATgOwybqvfRM/TGkmx+NrjOkH4CgA/cHj95AxxmuM8QJ4EMB+APoBOHrdfSVz3B3yczsOcD/eqRykxE4/n1ltj3U/s3UX3y4HMMFauwmACeu+l8zwDMLPi9yO536oP5c6HTy/kvT2DJzPe/W3NwYK6hLAWjvHWvtLtPc3xnQDUGSt/daycs1zAA5J1PikZSIc34MBvGKtrbTWLgAwD8D2677mWWvnW2urALyy7r6S2dyOt2QW/Xy2HgcDeHbd/5+F/s5mDGvtFwD+abTZ7XgeDOA5S98CaLfuPEvSlMvxdaO/vS4U1CXfBsaY6caYz40xg9dt6wFgUch9Fq3bJpmlB4CFId/XHUe37ZI5zlk3jeepkClbOq7ZQccxO1kAHxljphpjTl+3rYu1dum6//8FoEtqhiZx4nY89TOdPfS3NwY5qR5ApjLGfAKgq8NNV1lr33F52FIAva21K40xAwGMMcb0T9ggpdmaeXwlQ0U63uDUnRvAk8QbANwJ4OTkjU5EmmEXa+1iY0xnAB8bY34OvdFaa40x6umUJXQ8s5L+9sZIQV0zWWuHNOMxlQAq1/1/qjHmNwCbAlgMoGfIXXuu2yYp0pzjCx6zXiHfhx5Ht+2SBqI93saYxwG8t+7bSMdbMoeOYxay1i5e9+9yY8zb4PSsZcaYbtbapeum4y1P6SClpdyOp36ms4C1dlnd//W3NzqafplExphOdYs5jTEbgot456+bPrDGGDNoXdXL4wEoG5R5xgI4yhiTb4zZADy+3wOYDGATY8wGxpg8cIHv2BSOU2LQaC3GoWChHMD9eEtm0c9nljHGFBhj2tT9H8A+4M/tWAAnrLvbCdDf2UzndjzHAjh+XRXMQQBWh0zTlAyhv72xU6YuAYwxhwK4H0AnAO8bY36w1g4FsCuA640x1QCCAM601tYtDB0JVv/xA/hg3ZekIbfja62dbYx5DcBPAGoAnG2trV33mHMAjAfgBfCUtXZ2ioYvsbvdGLM1OAXkdwBnAECk4y2Zw1pbo5/PrNMFwNu8RoocAC9Zaz80xkwG8Jox5hQAfwA4IoVjlBgYY14GsDuA9YwxiwBcC+BWOB/PcQD2BwtolAE4KekDlpi4HN/d9bc3NobFFkVERERERCQTafqliIiIiIhIBlNQJyIiIiIiksEU1ImIiIiIiGQwBXUiIiIiIiIZTEGdiIiIiIhIBlNQJyIiIiIiksEU1ImIiIiIiGSw/wOnvJjN4TQH0gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model import RidgeClassifier\n",
    "\n",
    "import utils\n",
    "\n",
    "real = pd.DataFrame(data_np[:sample_size])\n",
    "\n",
    "model_real, model_fake = utils.test_real_vs_synthetic_data(real, synthetic, RidgeClassifier, tsne=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Example run in 97.597 s\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Classification \n",
    "coef = model_real.coef_.copy()\n",
    "plt.figure(figsize=(10, 5))\n",
    "scale = np.abs(coef).max()\n",
    "for i in range(10):\n",
    "    l1_plot = plt.subplot(2, 5, i + 1)\n",
    "    l1_plot.imshow(coef[i].reshape(28, 28), interpolation='nearest',\n",
    "                   cmap=plt.cm.RdBu, vmin=-scale, vmax=scale)\n",
    "    l1_plot.set_xticks(())\n",
    "    l1_plot.set_yticks(())\n",
    "    l1_plot.set_xlabel('Class %i' % i)\n",
    "plt.suptitle('Classification vector for...')\n",
    "\n",
    "run_time = time.time() - t0\n",
    "print('Example run in %.3f s' % run_time)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Example run in 97.912 s\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "coef = model_fake.coef_.copy()\n",
    "plt.figure(figsize=(10, 5))\n",
    "scale = np.abs(coef).max()\n",
    "for i in range(10):\n",
    "    l1_plot = plt.subplot(2, 5, i + 1)\n",
    "    l1_plot.imshow(coef[i].reshape(28, 28), interpolation='nearest',\n",
    "                   cmap=plt.cm.RdBu, vmin=-scale, vmax=scale)\n",
    "    l1_plot.set_xticks(())\n",
    "    l1_plot.set_yticks(())\n",
    "    l1_plot.set_xlabel('Class %i' % i)\n",
    "plt.suptitle('Classification vector for...')\n",
    "\n",
    "run_time = time.time() - t0\n",
    "print('Example run in %.3f s' % run_time)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
